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\nOur Products\n

Built on Our AI Engine

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Standalone products powered by the same vision and language models behind our enterprise solutions.

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\nTailored Solutions\n

Custom AI systems, engineered for your business

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When an off-the-shelf tool doesn't fit, we build one that does. Gekko Labs designs, trains and ships custom systems using the latest generative AI, computer vision, AI agents and retrieval-augmented generation. You work with the same engineers who build and run our own products, from the first workshop to production.

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\nWhat we build\n

Capabilities

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Generative AI & LLM Apps

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We build assistants, copilots and content pipelines on top of large language models, grounded in your own data and workflows. Prompting, fine-tuning and evaluation are designed in from the start, so output quality can be measured, not guessed.

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LLMsFine-tuningEvaluation
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AI Agents & Automation

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We design agents that plan, call your tools and APIs, and complete multi-step tasks, with guardrails and a human in the loop wherever the stakes are high. Repetitive back-office work becomes a monitored, auditable workflow.

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Tool callingOrchestrationHuman-in-the-loop
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RAG & Enterprise Knowledge

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We connect language models to your manuals, tickets, contracts and wikis through retrieval pipelines that cite their sources. Teams get precise answers from internal knowledge, and access controls stay intact.

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Vector searchHybrid retrievalCitations
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Computer Vision

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Detection, segmentation, tracking and recognition models trained on your imagery and tuned for your cameras and lighting. From quality inspection to identity checks, we turn video and images into reliable, structured signals.

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Document Intelligence

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We combine layout analysis, OCR and language models to read invoices, IDs, forms and handwritten notes, then deliver validated, structured data. Paper-heavy processes move from manual keying to straight-through processing with confidence scores.

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OCRLayout analysisData extraction
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Edge & MLOps Deployment

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We optimise and package models to run where they're needed, whether that's GPU servers, private cloud, mobile or embedded devices. Monitoring, retraining and versioning pipelines keep accuracy in check long after launch.

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QuantisationCI/CD for MLMonitoring
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\nWhy Gekko Labs\n

Built by a team that ships AI products

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Proven in our own products

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The same team builds and runs Gekko ID, Cyber Graph, Gekko Fitly and Gekko Wellio, so our methods have been tested in production, not just in slides.

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Edge to cloud

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We deploy wherever your use case needs it, from GPU clusters and private cloud to phones and embedded devices.

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Your data stays yours

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Models, code and data belong to you, and we can work entirely inside your infrastructure when privacy requires it.

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Model-agnostic

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We pick the best model for each job, whether open-source or commercial, and design systems so you can switch providers without starting over.

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\nHow we work\n

From idea to production

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Discover

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We map your goals, data and constraints, then pick the use cases where AI can deliver measurable value. You leave with a scoped plan and clear success criteria.

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Prototype

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Within weeks, a working prototype on your real data shows what's feasible and how well it performs, before larger budgets are committed.

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Build & integrate

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We harden the solution into production-grade software and connect it to your systems, APIs and user interfaces, with evaluation suites built in.

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Deploy & operate

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We ship to cloud, on-premise or edge, then monitor, retrain and improve the system as your data and needs evolve.

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\nEngagement & pricing\n

Pricing built around your project

Every AI project is different. Tell us what you want to achieve and our team will study it in detail and send you a clear, itemised proposal.

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\nStep 1\n

Discovery

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A short assessment of your goals, data and constraints to confirm feasibility and estimate the value.

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  • Use-case and data review
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  • Technical approach and risks
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  • Scoped plan with success metrics
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\nRecommended · Step 2\n

Pilot

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A fixed-scope, fixed-price project that proves the solution on your own data before you commit further.

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  • Fixed price, agreed upfront
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  • Model trained on your data
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  • Results measured against agreed KPIs
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\nStep 3\n

Production & scale

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Deployment, integration and ongoing operation of the solution across your sites and systems.

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  • Edge, on-premise or cloud
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  • Integration with your systems
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  • Monitoring, support and retraining
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\nRequest a proposal\n
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Looking to license Gekko ID, Cyber Graph, Gekko Fitly or Gekko Wellio? Use the same form and we will tailor a licence to your volume.

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\nWhy Gekko Labs\n

What you can expect from us

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Demonstrable results

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Success KPIs are agreed before we start, so every phase is judged on measurable outcomes.

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Transparent estimates

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Clear, itemised proposals with no hidden costs, and fixed prices for pilots.

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Senior team, lean structure

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Experienced engineers without big-consultancy overheads, so your budget goes into the solution.

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Built to reach production

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We design for deployment from day one, not just for a demo.

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\nHow it works\n

From request to kickoff

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Send your request

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Tell us about your goals, data and timeline using the form below.

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Discovery call

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We talk through your case with you, under NDA if you need it.

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Tailored proposal

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You receive a written proposal with scope, timeline, success metrics and cost.

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Kickoff

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Once you approve it, our team starts building with regular check-ins.

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\nRequest a proposal\n

Tell us about your project

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The more context you share, the more precise our proposal will be. Every request is reviewed personally by our engineering team.

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  • Your information is kept confidential
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  • NDA available on request
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  • Or write to us at info@gekkolabs.ai
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Industries our team has delivered AI for

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Banking & FinanceTelecommunicationsEnergyHealthcare & PharmaAutomotiveAerospace & DefenceFood & BeverageRail & TransportCybersecurityResearch & Academia
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\nFAQ\n

Frequently asked questions

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\nWhy don't you publish prices?\n

Every AI project depends on the data, the integration and the level of accuracy and support you need. Rather than a generic price list, we study your case and send a clear proposal with scope, timeline and cost.

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\nHow do pilots work?\n

A pilot is a fixed-scope, fixed-price project that proves value on your own data, with success criteria agreed before we start. You decide whether to move to production based on the results.

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\nCan you sign an NDA before we share details?\n

Yes. We are happy to sign an NDA before the discovery call or before you share any data.

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\nWhere does the solution run?\n

Wherever it makes sense for you: on edge devices, on your own servers or in the cloud provider you already use.

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\nWho owns the data and the models?\n

Your data remains yours and is only used for your project. Ownership and licensing of the delivered models and code are agreed transparently in the contract.

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\nDo you provide support after launch?\n

Yes. We offer ongoing monitoring, maintenance and model improvement so the system keeps performing as your data and needs evolve.

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\nCan we license your products?\n

Yes. Gekko ID, Cyber Graph, Gekko Fitly and Gekko Wellio are available under commercial licences, and they can be customised to your needs.

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\nTechnology\n

Our stack

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PyTorchHugging FaceLangGraphvLLMONNXTensorRTOpenCVQdrantFastAPIDockerKubernetesAWSAzureGCP
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Have a problem worth solving with AI?

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Tell us about your challenge and we'll come back with an honest view of what's possible and how we'd build it.

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\nOur products\n
\nGekko ID\nCyber Graph\nGekko Fitly\nGekko Wellio\n
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Gekko IDBanking & Fintech
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Gekko ID

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An identity verification SDK that onboards users with an ID document and a selfie: detects document tampering, blocks spoofing attempts and deepfakes, and extracts data via OCR from documents issued in any country.

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Get startedRequest a demo
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The complete experience

From ID card to verified customer in seconds

This is what your users see: they scan their document, take a quick selfie and they are in. Every check runs in the background while the experience stays simple.

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  1. Step 01Document capture and authenticity

    Guided capture gets a sharp image, and our AI checks the document has not been tampered with.

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  2. Step 02Data extraction

    OCR reads every field and the MRZ, and validates them automatically.

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  3. Step 03Selfie, liveness and anti-spoofing

    A short selfie proves a real, live person is present. Photos, screens, masks, deepfakes and injected video streams are rejected.

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  4. Step 04Face match and decision

    Face recognition matches the selfie to the ID photo and the user is approved in seconds.

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Contact us for a live walkthrough of the complete SDK with your own documents.

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\nTry it now\n

Read a Spanish ID card in a quarter of a second

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Here is one piece of Gekko ID you can test right away. Our ultra-light OCR pipeline runs a model with about one million parameters on a plain CPU, no GPU, and turns an ID card into clean, validated data: it checks the DNI control letter and the MRZ check digits, just as the full SDK does.

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Pick the front or back of the specimen card, or upload a photo of your own DNI.

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Choose a sample or upload an image and press Read document.

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The sample is the official specimen card. If you upload a real ID it is processed in memory and never stored; please only upload your own documents.

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This is a simplified example. The production SDK adds guided capture, tamper detection, liveness, deepfake detection, face matching and documents from any country. Ask us for a complete walkthrough.

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\nHow it works\n
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Capture and authenticate the ID

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Guided capture gets a sharp, glare-free image of the document. Our AI models then check that it is genuine: edited fields, replaced photos, reprinted cards and digital forgeries are flagged before any data is trusted.

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Selfie, liveness and face match

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A short selfie proves a real person is present. Anti-spoofing blocks printed photos, screen replays and masks, video injection detection stops virtual cameras and deepfake streams, and face recognition confirms the selfie matches the ID photo.

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Get a decision

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Your backend receives the extracted data together with the document authenticity, liveness, injection and face-match results, and a clear outcome to approve, review or reject.

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\nKey features\n
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Document tamper detection

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AI models spot edited fields, replaced photos, reprinted cards and digitally generated documents.

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Anti-spoofing and liveness

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Blocks printed photos, screen replays and masks presented instead of a real face.

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Deepfake and injection detection

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Detects deepfakes and face swaps, plus virtual cameras, emulators and injected video streams that bypass the real camera.

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Face recognition

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Matches the selfie to the photo on the document to confirm it is the same person.

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OCR data extraction

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Names, dates, document numbers and the MRZ extracted and validated automatically, ready to pre-fill your forms.

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Global document coverage

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Reads identity documents issued in any country, across scripts and layouts.

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Digital bank account openingKYC for fintech and paymentsCrypto and trading onboardingAge and identity checksInsurance and lending applicationsRe-verification of high-risk actions
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\nIntegration\n

Gekko ID ships as an SDK for your mobile and web apps, with the heavy lifting handled by our models. You keep control of the user journey and of where data is stored, so onboarding fits your brand and your compliance policies.

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Make onboarding fast and fraud-proof

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Talk to us about integrating Gekko ID into your onboarding flow.

\nRequest a demo\n
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\nOther products\n
\nCyber Graph\nGekko Fitly\nGekko Wellio\n
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\n\"Cyber\n
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Cyber Graph

\nIT & Security\n
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by Gekko Labs

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See every digital tool. Control every blind spot.

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Cyber Graph is an AI-powered platform for Shadow IT detection, asset intelligence, and IT governance. Discover what your business actually runs on, and take back control of your digital environment.

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\nThe Hidden Gap\n

Your business runs on more tools than you think.

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Cloud apps get adopted without approval. Teams subscribe to software on their own. Vendors and contractors connect to your systems in ways nobody fully tracks. Over time, your real digital environment drifts further and further from what leadership believes it looks like. That gap is called Shadow IT, and it quietly creates wasted spend, compliance exposure, security risk, and decisions made on incomplete information.

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Unmanaged SaaS subscriptions multiplying across teams

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Cloud services connecting to your data without oversight

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IT inventories that no longer reflect reality

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\nWhat is Cyber Graph\n

A continuous, evidence-based view of your digital environment.

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Instead of relying on manual inventories or partial dashboards, Cyber Graph builds a continuous, evidence-based picture of your real digital activity. It shows you what exists, what is changing, and what deserves attention, so leadership and IT teams can act with confidence. Cyber Graph helps companies discover the software, cloud services, and digital tools running across their environment, understand how they are used, and turn that visibility into governance, security, and smarter decisions.

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\nCore Capabilities\n

From digital blind spots to actionable clarity.

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01 / FULL VISIBILITY

See everything that runs.

Discover the software, cloud services, and digital tools actually running across your business, including the ones nobody declared.

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02 / SHADOW IT

Surface the unknown.

Identify unmanaged apps, unauthorised subscriptions, and unexpected external connections before they become a problem.

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03 / ASSET INTELLIGENCE

Beyond static inventories.

Understand which tools are used, by whom, and how they fit into your operations, so you can rationalise and optimise.

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04 / GOVERNANCE

Auditable by design.

Give leadership a clear, auditable view of your digital environment for compliance, internal control, and executive reporting.

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05 / AI INSIGHT

Practical AI, real signal.

Let AI surface patterns, anomalies, and priorities so your teams focus on what matters, not on noise.

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06 / HISTORICAL ANALYSIS

Look back with confidence.

Investigate incidents, justify decisions, and track how your environment evolves across weeks or months.

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\nThe Shift\n

Two ways to run your digital environment.

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Before Cyber Graph Guesswork and fragments

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  • IT inventories based on guesses and outdated lists
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  • Cloud apps adopted without anyone noticing
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  • Duplicate subscriptions quietly inflating costs
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  • Compliance questions answered with \"we think so\"
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  • Incidents investigated with missing context
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  • Leadership dependent on fragmented reports
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With Cyber Graph Evidence and control

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  • A live, evidence-based view of your digital environment
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  • Shadow IT surfaced early and managed with intent
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  • Wasted spend identified and rationalised
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  • Compliance answered with documented visibility
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  • Investigations supported by rich historical data
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  • Leadership equipped with one source of truth
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\nUse Cases\n

Built for the industries that cannot afford blind spots.

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Finance Visibility regulators expect

Banks, lenders, and financial services groups operate under strict regulatory pressure. Cyber Graph helps you maintain continuous visibility across systems, monitor sensitive data flows, and produce the kind of evidence regulators and auditors expect.

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Insurance One view, many moving parts

Insurance companies juggle legacy systems, distributed branches, and growing partner ecosystems. Cyber Graph brings these moving parts into a single view so risk, compliance, and IT teams stay aligned.

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Manufacturing Protect production continuity

Factories and industrial groups blend IT, operational systems, and external suppliers. Cyber Graph helps you map this complex landscape, detect unusual activity, and protect production continuity without slowing the business down.

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Public Sector Oversight that holds up

Public organisations manage sensitive data, multiple stakeholders, and high accountability standards. Cyber Graph strengthens oversight, supports governance frameworks, and gives leadership the clarity needed to make confident decisions.

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\nFor Everyone Who Decides\n

One platform. Two audiences. Aligned outcomes.

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For Executives Decisions backed by evidence

Get a clear, business-ready view of your digital environment. Understand where complexity is growing, where risks are hiding, and where your technology spend can be rationalised. Make decisions based on evidence, not assumptions.

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For IT & Security Governance you can act on

Strengthen governance, accelerate investigations, and explain risk in business terms. Replace scattered tools and partial inventories with a continuous, structured view of activity across your environment.

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Our Mission

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To empower organisations with complete cyber visibility, actionable intelligence, and the confidence to secure their digital ecosystem.

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Discover. Map. Understand. Secure.

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AI-powered Cyber Visibility & Risk Intelligence for modern enterprises.

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\nFAQ\n

Frequently asked questions

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What is Cyber Graph?

Cyber Graph is an AI-powered SaaS platform for Shadow IT detection, asset management, and IT governance, built by Gekko Labs for mid-market and enterprise organisations. It gives leadership and IT teams a clear, continuous view of the software, cloud services, and digital tools running across the business.

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What is Shadow IT, and why does it matter?

Shadow IT is the use of software, cloud services, apps, devices, or digital tools inside a company without full visibility or approval from leadership and IT. It creates hidden risks, duplicated spending, compliance exposure, and decisions made on incomplete information.

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How is Cyber Graph different from a traditional IT inventory?

Traditional inventories rely on manual lists that quickly become outdated. Cyber Graph builds a continuous, evidence-based view of your real digital activity, including the tools and services that were never formally declared.

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Who is Cyber Graph for?

Cyber Graph is designed for mid-market and enterprise organisations that need stronger visibility, governance, and control across their digital environment. It serves CEOs, CFOs, IT directors, security leaders, and compliance stakeholders.

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Does Cyber Graph support cybersecurity use cases?

Yes. Cyber Graph supports anomaly detection, historical investigation, asset risk reduction, and the kind of visibility security teams need to protect modern environments.

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Is Cyber Graph available in French and English?

Yes. Cyber Graph is fully bilingual and adapted to professional environments where both languages are used every day.

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How can I see Cyber Graph in action?

You can request a demo to see what Cyber Graph can reveal about your business.

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Ready to see what your business is really running?

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Most leaders are surprised by what their first assessment reveals. Take fifteen minutes to discover how much clarity you have been missing.

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\nOther products\n
\nGekko ID\nGekko Fitly\nGekko Wellio\n
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Gekko Fitly
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Gekko Fitly

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Upload a photo and browse a digital wardrobe to see exactly how an outfit looks on you before you buy.

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Get startedRequest a demo
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See it in action

Gekko Fitly in 70 seconds

Try on clothes from your own closet, ask the AI stylist for an outfit for any occasion, and add new garments with a single photo.

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Upload a photo

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The shopper uploads a single full-body photo, no special equipment or measurements needed.

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Browse the wardrobe

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They pick garments from a digital catalogue, just as they would in your online store.

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See it on you

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Our generative vision models render each outfit on the shopper's own photo, preserving their pose, shape and the garment's look.

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\nKey features\n
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Realistic try-on

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Generative AI drapes each garment naturally, keeping fabric, fit and details true to the product.

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Mix and match

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Combine tops, bottoms and outerwear to build complete outfits before buying.

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Catalogue-ready

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Works from your existing product images, so new collections can go live quickly.

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Web and mobile

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Embed the experience in your e-commerce site or app with a lightweight integration.

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\nUse cases\n
Fashion e-commerceMarketplaces and multi-brand storesBrand apps and lookbooksSocial and influencer campaignsIn-store smart mirrorsPersonal styling services
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Gekko Fitly plugs into your storefront through a simple integration, using the product photos you already have. Shoppers gain confidence in what they buy, and you get a more engaging, differentiated shopping experience.

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Let shoppers try before they buy

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Talk to us about bringing virtual try-on to your store.

\nRequest a demo\n
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\nOther products\n
\nGekko ID\nCyber Graph\nGekko Wellio\n
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Gekko AdjusterInsurTech
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Gekko Adjuster

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\n Unique & innovative\n Pioneer in Europe\n
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Home claims inspection and valuation guided by AI. The policyholder shows the damage from their phone, and Gekko Adjuster guides the inspection and prepares a report ready for your claims team, without waiting for three calendars to line up.

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Get startedRequest a demo
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See it in action

Gekko Adjuster in one minute

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\nHow it works\n
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A link by SMS

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Nothing to install. The policyholder joins when it suits them and gives consent on the first screen.

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A voice conversation and the camera

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The AI asks where the damage is, requests the evidence it needs and checks that every image is usable.

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A report for the claims handler

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Damage and evidence, valuation against your scale and points to review highlighted, sent to your system by API.

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\nKey features\n
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Connected by API

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Your claims system sends the file and the scale; Gekko Adjuster returns the report and the evidence.

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Human supervision

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Without consent or with insufficient data, the case goes to a person through your usual channel.

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Data under control

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Personal data protected, secure encrypted hosting, and explicit, recorded consent.

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Repairers arrive prepared

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Trades, expected time and the damage video are ready before the visit.

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\nUse cases\n
Water damageDamp and leaksHome insurance claimsAssistance networksRepair managementClaims triage
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Run a pilot with your claims team

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We scope the case together, compare results against on-site inspection and decide with data.

\nRequest a demo\n
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Gekko VoiceVoice AI
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Gekko Voice

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Everything you need to give your product a voice: expressive speech that sounds like a real person, agents that hold real-time conversations and a builder to create them in plain language.

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Get startedRequest a demo
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Gekko Kalima

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Text-to-speech that sounds like a real person, in 40+ languages and with the first audio in about 95 ms. Our model laughs, pauses, whispers and changes its tone with the context, so voice agents, content and customer calls finally sound natural.

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\nListen\n

Hear Gekko Kalima

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Pick a style or a language. The same voice changes its tone, emotion and pace with the context.

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Emotions and styles

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Gekko model · multilingual

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Pre-generated samples, female voice, produced with our Gekko models.

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\nHow it works\n
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\n01\n
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Send the text

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Any text through our API, with optional style and emotion tags when you want a specific delivery.

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Pick a voice

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Choose from the voice catalogue or create a brand voice of your own from a short recording.

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Stream the audio

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Speech starts playing before the sentence is finished, ready for live conversations.

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\nKey features\n
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Expressive by design

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Laughter, whispers, pauses and emphasis that make every line sound human, not read.

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Voice cloning

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A consistent brand voice created from a short sample, used across every channel.

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Real-time streaming

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First audio in about 95 ms over REST and WebSocket, so agents answer without awkward silences.

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40+ languages

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Natural, native-sounding voices in more than 40 languages, from Spanish and French to Arabic and Chinese.

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\nIntegration\n

Gekko Kalima is available through a simple REST and WebSocket API and SDKs, in our cloud or deployed in your own infrastructure.

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Gekko 1.5

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Real-time voice agents that listen and answer naturally. Speech in and speech out over a single connection, with interruptions, turn-taking and actions in the middle of the conversation.

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\nHow it works\n
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Connect

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Add the SDK to your website, app or phone line in a few lines of code.

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Converse

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The agent listens, understands and answers in real time, and lets people interrupt like in a real conversation.

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Act

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It calls your tools during the call: bookings, order lookups, CRM updates and hand-offs to a person.

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\nKey features\n
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Natural turn-taking

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Handles interruptions, pauses and changes of topic the way people actually talk.

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Tool calling

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Connects to your APIs and systems to get things done during the conversation.

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Multimodal

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Voice, text and camera input in the same session.

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SDKs for every stack

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Python, Node and React SDKs, plus mobile, to go live in days, not months.

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\nIntegration\n

Gekko 1.5 runs as a managed real-time API with SDKs for web, mobile and backend, and connects to your telephony and existing systems.

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Voice Agent Builder

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Describe the agent you need in plain language and get a production-ready voice agent with the right tone, knowledge and behaviour, without writing code.

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\nHow it works\n
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Describe it

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For example: “an agent that handles customer returns in a friendly tone”.

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Refine and test

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Adjust the voice, the instructions and the knowledge it uses, and talk to it right away.

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Publish

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Deploy it to your phone line, website or app with one click.

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\nKey features\n
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Plain-language setup

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Build and change agents by describing what you want, no code needed.

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Knowledge and tools

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Connect documents, FAQs and your systems so the agent answers with your information.

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Team collaboration

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Your team edits voices and agents together, with changes published instantly.

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One-click deployment

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From idea to a live agent in minutes, on the channels you already use.

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\nIntegration\n

Voice Agent Builder runs on Gekko Kalima and Gekko 1.5, so every agent you create speaks with expressive voices and answers in real time.

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\nUse cases\n
Voice agents and call centresAppointment bookingAudiobooks and podcastsAdvertising and dubbingE-learningAccessibilityIn-app assistantsInternal helpdesks
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Give your product a voice people enjoy

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Talk to us about your use case and hear Gekko Voice live.

\nRequest a demo\n
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\n Back to all products\n
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Gekko Wellio
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Gekko Wellio

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A wellbeing check-in that takes 30 seconds and only needs a selfie. Gekko Wellio reads wellness indicators such as heart rate and breathing from the phone camera, then turns them into food and product recommendations your users actually act on.

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Get startedRequest a demo
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See it in action

From selfie to personalised advice in seconds

No wearables, no extra hardware. The user looks at the camera, Gekko Wellio does the rest and answers with a clear summary and recommendations tailored to their readings.

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30 s
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for a complete check-in with the phone users already carry

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0
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wearables or extra devices needed

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1 tap
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from insight to the recommended products in your catalogue

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\nWhy partners choose Gekko Wellio\n
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Turns wellbeing into sales

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Recommendations link straight to products in your catalogue, so every check-in becomes a personalised shopping moment.

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Brings users back

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A quick daily or weekly check-in builds a habit, and progress over time gives users a reason to return.

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Works on any smartphone

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Runs with the front camera, on iOS, Android and the web, inside your own app and under your brand.

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Privacy first

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The camera stream is processed only to produce the readings, and the data stays under the control of you and your users.

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\nTry it now\n

Take your own 20-second check-in

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Here you can try one part of the Gekko Wellio app: the contactless reading. Turn on your camera, look at the screen for 20 seconds and our model estimates your heart rate, heart-rate variability, breathing rate and stress level from the subtle changes in your face.

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Good light, face the camera and stay still

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Your video is analysed and discarded straight away; nothing is stored.
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Wellness demo for illustration only, not a medical device. Readings are estimates and can be affected by light, movement and camera quality. The full Gekko Wellio app adds personalised food and product recommendations; contact us to see it.

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\nHow it works\n
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Look at the camera

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The user takes a short selfie scan with the front camera of their phone. No wearables, no setup, under a minute from start to finish.

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Read the signals

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Our AI models read the subtle signals in the face that change with every heartbeat and breath, and estimate wellness indicators such as heart rate, breathing rate, heart-rate variability and stress level.

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Turn insights into action

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Gekko Wellio translates the readings into a clear summary and personalised suggestions for foods and products from your catalogue that support healthier habits.

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\nKey features\n
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Contactless wellness indicators

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Heart rate, breathing rate, heart-rate variability and stress level from a selfie, with no extra devices.

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Personalised recommendations

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Suggestions matched to each user's readings and goals, linked to the products you sell.

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Progress over time

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Repeat check-ins build a picture of how each user's wellbeing evolves, a strong reason to come back.

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White-label SDK

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Embed Gekko Wellio in your own app or website with your branding and your user journey.

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\nUse cases\n
Wellness and lifestyle appsNutrition and food retailInsurance wellbeing programmesCorporate wellnessPharmacy and health retailFitness platforms
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\nIntegration\n

Gekko Wellio can be embedded in partner apps and digital channels, turning a simple selfie into an engaging, personalised wellbeing check-in. Gekko Wellio is a wellness tool and is not intended to diagnose or treat any medical condition.

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Bring wellbeing insights to your users

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Talk to us about embedding Gekko Wellio in your app or programme.

\nRequest a demo\n
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\nOther products\n
\nGekko ID\nCyber Graph\nGekko Fitly\n
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\nApplied Intelligence\n

Solutions by Industry

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Pick a sector to see what vision AI can do for it, with example use cases and how we deliver.

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\n Back to all solutions\n\n
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Smart Logistics

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Gekko Labs gives ports and logistics hubs a live picture of everything moving on the dock. Our multi-object detection tracks vehicles, vessels and personnel across existing camera feeds, turning busy yards into measurable, safer and better-coordinated operations.

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Get startedRequest a demo
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\nLogistics\nLive demoDock Occupancy Tracking\n\n
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Read any shipping label at a glance

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Pick a parcel on the conveyor. Our model finds the label at any angle, straightens it, decodes the barcode and QR code, reads every field and checks that all sources agree.

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\nGet started\nRequest a demo\n
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\"Parcel
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Input
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Tracking number
–
Service
–
Weight
–
Inference time
–
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JSON output
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Run inferenceRunning…Run againReady. Pick an example and press Run inference.Inference completemeasuredInputResultLoading model weightsLocating and straightening the labelDecoding barcode and QR codeReading every fieldCross-checking the tracking numberGekko document model
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\nLogistics\n
Busy docks, limited visibility
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Ports and yards mix heavy vehicles, vessels and people in tight, constantly changing spaces. Operators rely on radio calls and manual checks to know where everything is. That makes congestion hard to anticipate and safety risks hard to catch in time.
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    \n
  • Vessel and vehicle tracking. Detect and follow trucks, cranes, vessels and equipment across every camera on the terminal.
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  • Personnel safety zones. Flag people entering hazardous zones near moving machinery before an incident occurs.
    • \n
  • Throughput insights. Measure dwell times, queues and berth activity to find and remove bottlenecks.
    • \n
  • Edge-ready performance. Models run on site, keeping latency low and video on your own network.
    • \n
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\n\"Multi-Object\nMulti-Object Detection\n
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Use cases
Vision AI in action
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\n\"Container\n
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Container Yard Counting
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A camera on a yard truck detects each intermodal container along with its ID, logo and chassis markings, counting units as they pass a virtual line. Terminals build a live yard inventory without clipboard walks, so lost or misplaced containers are found in minutes.
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Object DetectionObject CountingContainer ID
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\n\"Aerial\n
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Aerial Vessel Detection
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Oriented bounding boxes capture every vessel and berth in drone or satellite imagery, following each hull's true angle even in crowded harbors. Port authorities get automatic berth occupancy and vessel counts for planning and traffic monitoring.
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OBB DetectionAerial ImageryMaritime
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\n\"Forklift\n
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Forklift & Pallet Tracking
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Forklifts and pallets are detected and tracked across the warehouse floor, with dwell time measured in each zone. Spot congestion, idle equipment and slow handoffs before they delay outbound loads.
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Object TrackingDwell TimeYard Operations
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\n\"Yard\n
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Yard Stall Reading
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Dock and stall numbers are read from drone footage, so every trailer in the yard is mapped automatically.
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AerialOCRDetection
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\nHow we work\n
From pilot to production
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01
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Connect dock cameras
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We plug into your existing CCTV and PTZ cameras across berths, gates and yards without replacing infrastructure.
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02
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Tune multi-object detection
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We train detection and tracking models on your terminal's vehicles, vessels, equipment and lighting conditions.
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03
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Deploy and integrate
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Models run on edge or cloud and feed events into your TOS, VMS or dashboards, with ongoing monitoring and model updates.
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See your terminal in real time
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Talk to our team about turning your dock cameras into live operational intelligence.
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Get startedRequest a demo
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\n Back to all solutions\n\n
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Energy & Environmental Monitoring
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Gekko Labs turns thermal, infrared and optical feeds into continuous environmental monitoring. Our segmentation models outline oil spills, leaks and hot spots pixel by pixel, then trigger alerts the moment something changes, so teams respond in minutes instead of discovering problems hours later.
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Get startedRequest a demo
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\nEnergy\nLive demoOil Spill Segmentation\n\n
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Map rooftop solar potential
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Pick an aerial photo. Our model finds every roof from a single word, cuts out its exact footprint and turns it into installable capacity and yearly energy, roof by roof.
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\nGet started\nRequest a demo\n
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\"Aerial
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Input
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Roofs found
–
Roof area
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Installable capacity
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Energy per year
–
Estimate based on stated assumptions (ground resolution, 60 % usable roof, 0.2 kWp/m², 1,500 kWh/kWp per year). A site survey confirms the final design.
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JSON output
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Run inferenceRunning…Run againReady. Pick an example and press Run inference.Inference completemeasuredInputResultLoading model weightsFinding every roofSegmenting roof footprintsEstimating capacity and yieldGekko geospatial model
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\nEnergy\n
Large sites, small windows to react
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Terminals, pipelines and offshore assets cover vast areas that operators cannot watch continuously. Spills and leaks are often hard to see with the naked eye, especially at night or on water. Every minute of delay increases environmental impact, cleanup cost and regulatory exposure.
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    \n
  • Thermal-IR segmentation. Precise spill and hot-spot outlines from infrared imagery, day or night, in poor visibility.
    • \n
  • Automated spill alerting. Detections become instant alerts with location, extent and imagery sent to the right responders.
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  • Around-the-clock coverage. Models watch every feed continuously, removing gaps between manual patrols and inspections.
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  • Audit-ready evidence. Every event is logged with time-stamped imagery to support reporting and compliance reviews.
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\n\"Automated\nAutomated Spill Alerting\n
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Use cases
Vision AI in action
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\n\"Solar\n
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Solar Hotspot Detection
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Drone-mounted thermal cameras sweep entire solar farms while the model flags overheating cells and failing modules frame by frame. Crews go straight to the faulty panels instead of walking every row, cutting inspection time and recovering lost generation sooner.
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Object DetectionThermal ImagingDrone Inspection
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\n\"Grid\n
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Grid Asset Thermal Inspection
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Thermal imagery of poles and lines is scanned for components running abnormally hot, with each hotspot boxed and its peak temperature reported. Utilities catch failing connectors and transformers before they trip, reducing outages and emergency call-outs.
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Thermal ImagingAnomaly DetectionPower Lines
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\n\"Storage\n
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Storage Tank Mapping
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Oriented bounding boxes pick out every storage tank in aerial footage of tank farms and terminals, even when packed tightly together. Operators get an automatic asset inventory and a quick baseline for spotting changes, leaks or new construction across large sites.
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OBB DetectionAerial ImageryAsset Inventory
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\n\"Emission\n
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Emission & Steam Monitoring
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Instance segmentation outlines steam and smoke plumes rising from stacks and process units in real time. Continuous visual monitoring helps refineries and plants catch abnormal releases early and document emissions compliance without manual watch rounds.
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Instance SegmentationEmissionsProcess Safety
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\n\"Solar\n
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Solar Array Survey
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Individual solar panels are detected and counted from aerial imagery for asset inventory and inspection.
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AerialDetectionCounting
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\n\"Tank\n
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Tank Farm Monitoring
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Storage tanks are located and inventoried across oil and gas terminals from satellite or drone imagery.
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AerialDetection
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\nHow we work\n
From pilot to production
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01
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Connect thermal feeds
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We integrate your existing thermal, IR and optical cameras, or help specify new ones for the areas that matter most.
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02
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Train on your site
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We fine-tune segmentation models on imagery from your assets, water surfaces and weather conditions so they recognise real events, not reflections.
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03
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Deploy and alert
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Models run on edge hardware close to the cameras and push alerts into your control room, SCADA or incident-response workflow, with ongoing monitoring and retraining.
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Protect your sites with vision AI
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Tell us about your assets and cameras, and we will scope a monitoring pilot with you.
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Get startedRequest a demo
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\n Back to all solutions\n\n
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Document Intelligence
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Gekko Labs combines OCR, layout analysis and vision-language models to read documents the way people do. Invoices, forms, contracts and technical drawings become clean, structured data that flows straight into your systems, with humans reviewing only what truly needs attention.
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Get startedRequest a demo
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\nDocument Intelligence\nLive demoDocument digitisation\n\n
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\nLive demo\n
Try it on your own document
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\nVision-Language Model\n
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\nOutput\n\n
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Upload a document and pick a task to see the model's output here.
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Runs on a compact model on CPU, so the first request can take up to a minute while it wakes up. Images are processed in memory and never stored. Please don't upload documents that contain personal data; use a sample or a redacted copy.
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\nDocument Intelligence\n
Manual data entry does not scale
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Teams still retype information from scanned forms, emails and PDFs into business systems. Layouts vary by supplier, country and year, which breaks template-based tools. The result is slow processing, costly errors and skilled staff stuck on repetitive work.
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    \n
  • Accurate field extraction. Pull totals, dates, IDs and line items from varied layouts without rigid templates.
    • \n
  • Multilingual understanding. VLMs read documents in multiple languages, handwriting styles and scan qualities.
    • \n
  • Human-in-the-loop review. Low-confidence fields are routed to reviewers, so automation never hides uncertainty.
    • \n
  • Private deployment. Run on premises or in your cloud tenant to keep sensitive documents under your control.
    • \n
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\n\"Layout\nLayout Detection\n
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Use cases
Vision AI in action
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\n\"Handwriting\n
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Handwriting OCR
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Every handwritten line is located, ordered and transcribed, even on lined notebooks and cluttered forms. Turn archives of handwritten notes, delivery slips and signed paperwork into searchable, structured text.
\n
OCRHandwritingText Detection
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\n\"Table\n
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Table & Formula Parsing
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Complex tables with merged cells and embedded equations are rebuilt as clean, editable Markdown and LaTeX. No more retyping figures from reports: the output drops straight into spreadsheets, databases or LLM pipelines.
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Table RecognitionFormula OCRMarkdown Export
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\n\"Document\n
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Document Layout Parsing
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Any page is broken into text, tables, figures and formulas, then rebuilt as clean structured output.
\n
Layout AnalysisOCR
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\nHow we work\n
From pilot to production
\n
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01
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Collect sample documents
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We start with a representative set of your real documents and agree on the fields and outputs that matter.
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02
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Adapt models to you
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We fine-tune extraction and VLM pipelines on your formats and validate accuracy against your own ground truth.
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03
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Integrate and scale
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We connect the pipeline to your ERP, DMS or workflow tools via API, then monitor quality and keep improving it.
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Automate your document workflows
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Share a few sample documents and we will show you what can be extracted automatically.
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Get startedRequest a demo
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\n Back to all solutions\n\n
\n
Aerospace Intelligence
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Gekko Labs brings computer vision to aerospace inspection, maintenance and production. Our models detect surface defects, verify assemblies and document component condition consistently, helping teams meet demanding quality standards without slowing down the line or the hangar.
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Get startedRequest a demo
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\nAerospace\nLive demoAerial OBB Detection\n\n
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Count every aircraft from orbit
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Pick a satellite image of an airport. Our model detects each aircraft with an oriented box that follows its fuselage, estimates its heading and counts the apron in a fraction of a second.
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\nGet started\nRequest a demo\n
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\n
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\"Satellite
\"\"
Input
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\n\n
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Aircraft
–
Helicopters
–
Mean confidence
–
Inference time
–
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JSON output
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Run inferenceRunning…Run againReady. Pick an example and press Run inference.Inference completemeasuredInputResultLoading model weightsPreparing the satellite tileDetecting aircraft with oriented boxesEstimating headingsGekko aerial vision model
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\nAerospace\n
Zero tolerance, limited inspectors
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Aerospace components must meet strict safety and quality requirements, yet visual inspection remains largely manual. Experienced inspectors are scarce, and fatigue leads to inconsistency across shifts. Every hour an aircraft spends grounded for checks carries a real operational cost.
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    \n
  • Fine defect detection. Find cracks, dents, corrosion and coating flaws that are easy to miss by eye.
    • \n
  • Faster MRO inspections. Speed up visual checks on fuselage, engines and components during maintenance turnarounds.
    • \n
  • Assembly verification. Confirm fasteners, connectors and parts are present and correctly installed.
    • \n
  • Traceable records. Store annotated images with each inspection to support certification and audits.
    • \n
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\n
\n\"Apron\nApron Operations\n
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\n
Use cases
Vision AI in action
\n
\n
\n
\n
\n\"Turbine\n
\n
\n
Turbine Crack Detection
\n
Hairline cracks and surface damage on engine fan blades are flagged automatically during borescope and visual inspections. Inspectors get a consistent second pair of eyes, catching defects before they become costly failures.
\n
Defect DetectionMRO InspectionQuality Control
\n
\n
\n
\n
\n\"Part\n
\n
\n
Part Feature Verification
\n
Every cut-out, rivet hole and threaded insert on an airframe part is detected and checked against its specification. Missing or misplaced features are caught at the workstation, not at final assembly.
\n
Object DetectionAssembly VerificationQuality Control
\n
\n
\n
\n
\n\n
\nHow we work\n
From pilot to production
\n
\n
\n
01
\n
Capture inspection imagery
\n
We work with your existing inspection cameras, borescopes or drones, and define capture setups where needed.
\n
\n
\n
02
\n
Train on your defects
\n
We build segmentation and detection models on your parts and defect classes, validated with your quality engineers.
\n
\n
\n
03
\n
Deploy with traceability
\n
Models run on edge stations or secure cloud and integrate with your MES or MRO systems, with versioned models and ongoing support.
\n
\n
\n
\n\n
\n
\n
\n
\n
Raise your inspection standard
\n
Talk to our team about a vision pilot for your production line or maintenance hangar.
\n
\n
Get startedRequest a demo
\n
\n
\n
\n\n
\n Back to all solutions\n\n
\n
Automotive Intelligence
\n
\n
Gekko Labs helps automotive manufacturers and suppliers inspect every part, weld and finish as it moves down the line. Our models run in real time on edge hardware, catching defects early and verifying assemblies before they reach the next station.
\n
Get startedRequest a demo
\n
\n
\n
\n
\n\n
\nAutomotive\nLive demoComponent Segmentation\n\n
\n
\n
\n
\n
\n
See the road like an ADAS system
\n
Pick a dashcam frame. Our model detects every road user, estimates depth from a single camera, ranges each object and draws a bird's-eye view of the scene.
\n
\n
\nGet started\nRequest a demo\n
\n
\n
\n
\n
\n
\n
\"Dashcam
\"\"
Input
\n
\n\n
\n
\n
Road users
–
Pedestrians and riders
–
Nearest object
–
Inference time
–
\n
JSON output
\n
\n
\n
\n
Run inferenceRunning…Run againReady. Pick an example and press Run inference.Inference completemeasuredInputResultLoading model weightsDetecting road usersEstimating depth from one cameraRanging every objectBuilding the bird's-eye viewGekko driving perception model
\n
\n\n
\n
\nAutomotive\n
High volume, tight tolerances
\n
Automotive lines produce huge volumes with very little room for error. Manual inspection struggles to keep up with cycle times and model variants. Defects found late lead to rework, scrap and recalls that are far more expensive than catching them at the source.
\n
    \n
  • Paint and body inspection. Detect scratches, dents and paint defects on body panels consistently, shift after shift.
    • \n
  • Assembly verification. Check that components, clips and connectors are present and correctly positioned.
    • \n
  • Real-time at the line. Edge inference keeps pace with production without adding cycle time.
    • \n
  • Worker safety. Monitor PPE and restricted zones around robots and heavy equipment.
    • \n
\n
\n
\n\"Car\nCar Parts Segmentation\n
\n
\n\n
\n
\n
Use cases
Vision AI in action
\n
\n
\n
\n
\n\"Plate\n
\n
\n
Plate Detection
\n
License plates are located on moving vehicles for access control and tolling.
\n
DetectionANPR
\n
\n
\n
\n
\n\n
\nHow we work\n
From pilot to production
\n
\n
\n
01
\n
Connect line cameras
\n
We integrate with your existing industrial cameras and PLCs, or help design inspection stations where coverage is missing.
\n
\n
\n
02
\n
Train on your variants
\n
We fine-tune detection and segmentation models on your parts, finishes and defect types across model variants.
\n
\n
\n
03
\n
Deploy and integrate
\n
Models run on edge devices at the station and report to your MES or quality systems, with monitoring and retraining as products change.
\n
\n
\n
\n\n
\n
\n
\n
\n
Bring vision AI to your line
\n
Tell us about your inspection points and we will scope a pilot that fits your production.
\n
\n
Get startedRequest a demo
\n
\n
\n
\n\n
\n Back to all solutions\n\n
\n
Consumer Goods Intelligence
\n
\n
Gekko Labs gives consumer goods producers automated eyes on packaging, labelling and product quality. Our models check every unit at line speed, so the product that reaches the shelf matches your brand standards every time.
\n
Get startedRequest a demo
\n
\n
\n
\n
\n\n
\nConsumer Goods\nLive demoLabel Inspection\n\n
\n
\n
\n
\n
\n
Turn a phone photo into a catalogue shot
\n
Pick a product photo taken at home. Our model isolates the product with pixel-accurate edges, even fine laces and reflections, and places it in a clean studio scene with a natural shadow.
\n
\n
\nGet started\nRequest a demo\n
\n
\n
\n
\n
\n
\n
\"Product
\"\"
Input
\n
\n\n
\n
\n
Soft-edge pixels refined
–
Output resolution
–
Product detection
–
Inference time
–
\n
JSON output
\n
\n
\n
\n
Run inferenceRunning…Run againReady. Pick an example and press Run inference.Inference completemeasuredInputResultLoading model weightsLocating the productComputing a pixel-accurate matteComposing the studio shotGekko product imaging model
\n
\n\n
\n
\nConsumer Goods\n
Many SKUs, constant change
\n
Consumer goods lines run at high speed across many products and frequent packaging updates. Rule-based vision systems are costly to reconfigure for every change. Small errors in labels or packaging can trigger returns, retailer penalties and damage to brand trust.
\n
    \n
  • Label and print checks. Verify labels, dates, barcodes and print quality on every item.
    • \n
  • Packaging integrity. Detect damaged, misaligned, open or underfilled packages before they ship.
    • \n
  • SKU flexibility. Adapt models quickly to new products, seasonal designs and packaging changes.
    • \n
  • Line performance insights. Track defect trends by line and shift to target root causes.
    • \n
\n
\n
\n\"Cap\nCap Counting\n
\n
\n\n
\n
\n
Use cases
Vision AI in action
\n
\n
\n
\n
\n\"Seal\n
\n
\n
Seal Defect Detection
\n
Damaged lids, broken seals and dented caps are detected automatically as products move down the line. Catch defects at the source and stop a single bad pack from shipping.
\n
Defect DetectionQuality ControlPackaging
\n
\n
\n
\n
\n\"Bottle\n
\n
\n
Bottle Line Throughput
\n
Every bottle is tracked through production to measure throughput live.
\n
TrackingCounting
\n
\n
\n
\n
\n\"Pack\n
\n
\n
Pack Verification
\n
Each pack is verified as complete before it leaves the line.
\n
DetectionQA
\n
\n
\n
\n
\n\n
\nHow we work\n
From pilot to production
\n
\n
\n
01
\n
Connect your lines
\n
We use your existing inspection cameras or add compact capture points at key packaging stations.
\n
\n
\n
02
\n
Train per product family
\n
We fine-tune models on your SKUs and defect examples, designed to adapt quickly as designs change.
\n
\n
\n
03
\n
Run and improve
\n
Models run on edge at the line, trigger rejects and report to your MES, with ongoing retraining for new products.
\n
\n
\n
\n\n
\n
\n
\n
\n
Protect your brand on the line
\n
Talk to our team about automating quality checks across your product range.
\n
\n
Get startedRequest a demo
\n
\n
\n
\n\n
\n Back to all solutions\n\n
\n
Vision AI for Healthcare
\n
\n
Gekko Labs builds vision and document AI that helps healthcare teams work faster and more consistently. From medical imaging support to patient monitoring and clinical paperwork, our models are designed to assist professionals, with privacy and human oversight built in from day one.
\n
Get startedRequest a demo
\n
\n
\n
\n
\n\n
\nHealthcare\nLive demoSurgical Instrument Segmentation\n\n
\n
\n
\n
\n
\n
Segment a whole-body CT into 3D anatomy
\n
Run our medical imaging model on an anonymised CT scan from a public research dataset. It labels more than a hundred structures voxel by voxel, measures their volumes and rebuilds the anatomy in 3D. Research demonstration, not for diagnosis.
\n
\n
\nGet started\nRequest a demo\n
\n
\n
\n
\n
\n
\n
Drag to rotate · scroll to zoom
Input
\n
\n\n
\n
\n
Structures segmented
–
Inference time
–
Show in 3D
Largest organs (volume)
    \n
    JSON output
    \n
    \n
    \n
    \n
    Run inferenceRunning…Run againReady. Pick an example and press Run inference.Inference completemeasuredInputResultLoading model weightsResampling the CT to 1.5 mm voxelsSegmenting anatomical structuresBuilding 3D surfacesMeasuring organ volumesGekko medical imaging modelminLiverSpleenLeft kidneyRight kidneyStomachPancreasHeartBrainAortaBladderGallbladderSmall bowelColonLungs (5 lobes)
    \n
    \n\n
    \n
    \nHealthcare\n
    Stretched staff, growing data
    \n
    Clinical teams face rising volumes of images, documents and patients with limited time and staff. Manual review is slow and varies from person to person. Valuable information stays locked in images and paperwork instead of reaching the people who need it.
    \n
      \n
    • Imaging assistance. Highlight regions of interest in medical images to support, not replace, clinical review.
      • \n
    • Patient monitoring. Detect falls, movement and room events to help staff respond sooner.
      • \n
    • Clinical document processing. Extract structured data from referrals, forms and reports to reduce administrative load.
      • \n
    • Privacy by design. On-premises or private-cloud deployment keeps patient data inside your environment.
      • \n
    \n
    \n
    \n\"Dental\nDental X-ray Analysis\n
    \n
    \n\n
    \n
    \n
    Use cases
    Vision AI in action
    \n
    \n
    \n
    \n
    \n\"Pill\n
    \n
    \n
    Pill Detection & Counting
    \n
    Every tablet and capsule is located and counted in a single pass, regardless of shape or colour. Automate pharmacy QA, dispensing checks and blister-pack verification with near-instant results.
    \n
    Object DetectionObject CountingPharma QA
    \n
    \n
    \n
    \n
    \n\"Rehab\n
    \n
    \n
    Rehab Exercise Tracking
    \n
    Pose keypoints follow the body to count repetitions and measure joint angles in real time. Patients get guided physiotherapy at home while clinicians receive objective progress data.
    \n
    Pose EstimationWorkout MonitoringRemote Care
    \n
    \n
    \n
    \n
    \n\n
    \nHow we work\n
    From pilot to production
    \n
    \n
    \n
    01
    \n
    Define the clinical need
    \n
    We work with your clinicians and IT to select a focused use case, data sources and privacy requirements.
    \n
    \n
    \n
    02
    \n
    Develop with oversight
    \n
    We train and validate models on de-identified data, with clinicians reviewing outputs throughout.
    \n
    \n
    \n
    03
    \n
    Deploy securely
    \n
    Models run on premises or in a private cloud and integrate with your EHR or PACS, with monitoring and ongoing support.
    \n
    \n
    \n
    \n\n
    \n
    \n
    \n
    \n
    Explore AI for your care setting
    \n
    Talk to our team about a secure, clinically guided pilot for your organisation.
    \n
    \n
    Get startedRequest a demo
    \n
    \n
    \n
    \n\n
    \n Back to all solutions\n\n
    \n
    Smart Manufacturing
    \n
    \n
    Gekko Labs brings custom computer vision to the factory floor. We turn the cameras on your lines into automated inspectors that spot defects, verify assemblies and monitor safety in real time, running on edge hardware right where production happens.
    \n
    Get startedRequest a demo
    \n
    \n
    \n
    \n
    \n\n
    \nManufacturing\nLive demoConveyor Carton Inspection\n\n
    \n
    \n
    \n
    \n
    \n
    Find defects it has never seen
    \n
    No defect examples needed: our model learns what a good part looks like from a few dozen photos, then highlights anything that deviates, from scratches to missing components. Drag the divider to compare.
    \n
    \n
    \nGet started\nRequest a demo\n
    \n
    \n
    \n
    \n
    \n
    \n
    \"Part
    \"\"
    Input
    \n
    \n\n
    \n
    \n
    Anomaly score (threshold 1.0)
    –
    Defect area
    –
    Defect regions
    –
    Inference time
    –
    \n
    JSON output
    \n
    \n
    \n
    \n
    Run inferenceRunning…Run againReady. Pick an example and press Run inference.Inference completemeasuredInputResultLoading model weightsLearning normal appearance from good partsExtracting multi-scale featuresComparing with the memory of good partsGekko anomaly detection model
    \n
    \n\n
    \n
    \nManufacturing\n
    Manual inspection cannot keep pace
    \n
    Human inspectors get tired, and sampling-based checks let defects slip through. Traditional machine vision is rigid and expensive to adapt when products change. Defects caught late mean scrap, rework and unhappy customers.
    \n
      \n
    • Automated defect detection. Catch surface flaws, missing features and dimensional issues before parts move downstream.
      • \n
    • Process monitoring. Watch machines and workstations to detect jams, anomalies and deviations early.
      • \n
    • Safety compliance. Monitor PPE use and restricted zones to keep people safe around machinery.
      • \n
    • Edge inference. Low-latency models run on site, even without a reliable internet connection.
      • \n
    \n
    \n
    \n\"Production\nProduction Line Monitoring\n
    \n
    \n\n
    \n
    \n
    Use cases
    Vision AI in action
    \n
    \n
    \n
    \n
    \n\"Bottle\n
    \n
    \n
    Bottle Cap & Label QA
    \n
    Each bottle is counted as it passes while caps and labels are verified on the moving belt. Missing caps or misapplied labels trigger instant alerts without slowing production.
    \n
    Object DetectionObject CountingQuality Control
    \n
    \n
    \n
    \n
    \n\"Conveyor\n
    \n
    \n
    Conveyor Counting
    \n
    Products are counted automatically as they cross the line, keeping production on target.
    \n
    CountingTracking
    \n
    \n
    \n
    \n
    \n\n
    \nHow we work\n
    From pilot to production
    \n
    \n
    \n
    01
    \n
    Connect your cameras
    \n
    We start with the cameras you already have on the line, adding capture points only where coverage is missing.
    \n
    \n
    \n
    02
    \n
    Train on your parts
    \n
    We fine-tune detection and segmentation models on your products and defect types, validated with your quality team.
    \n
    \n
    \n
    03
    \n
    Deploy and integrate
    \n
    Models run on edge devices and connect to your MES, PLCs and dashboards, with continuous monitoring and retraining.
    \n
    \n
    \n
    \n\n
    \n
    \n
    \n
    \n
    Automate your quality control
    \n
    Tell us about your line and we will design a pilot around your toughest inspection problem.
    \n
    \n
    Get startedRequest a demo
    \n
    \n
    \n
    \n\n
    \n Back to all solutions\n\n
    \n
    Media & Sports Analytics
    \n
    \n
    Gekko Labs helps media companies make sense of huge video and image libraries. Our detection models and VLMs tag scenes, objects, text and people automatically, so archives become searchable and production workflows move faster.
    \n
    Get startedRequest a demo
    \n
    \n
    \n
    \n
    \n\n
    \nMedia\nLive demoLive Sports Detection\n\n
    \n
    \n
    \n
    \n
    \n
    Follow any player through the clip
    \n
    Pick a clip and a target. Our video model locks on to it in the first frame and keeps its exact silhouette through fast motion, occlusions and camera moves, ready for highlights, graphics or analytics.
    \n
    \n
    \nGet started\nRequest a demo\n
    \n
    \n
    \n
    \n
    Pick a target (outlined on the first frame)
    \n
    \n
    Input
    \n
    \n\n
    \n
    \n
    Frames tracked
    –
    Coverage
    –
    Path length
    –
    Time per frame
    –
    \n
    JSON output
    \n
    \n
    \n
    \n
    Run inferenceRunning…Run againReady. Pick an example and press Run inference.Inference completemeasuredInputResultLoading model weightsDecoding the clipLocking on to the selected targetFollowing it frame by frameframesGekko video segmentation model
    \n
    \n\n
    \n
    \nMedia\n
    Too much content, too little metadata
    \n
    Media organisations generate and store more footage than teams can ever tag by hand. Without good metadata, valuable content sits unused in archives. Manual logging and moderation slow down production and increase the risk of publishing errors.
    \n
      \n
    • Automated tagging. Generate rich metadata for scenes, objects and on-screen text across your library.
      • \n
    • Searchable archives. Find the exact clip or image with natural-language search powered by VLMs.
      • \n
    • Content moderation. Flag sensitive or non-compliant content before it is published.
      • \n
    • Faster production. Speed up logging, highlight selection and clip preparation for editorial teams.
      • \n
    \n
    \n
    \n\"Action\nAction Pose Tracking\n
    \n
    \n\n
    \n
    \n
    Use cases
    Vision AI in action
    \n
    \n
    \n
    \n
    \n\"Text-Prompted\n
    \n
    \n
    Text-Prompted Object Tracking
    \n
    Any object described in plain language is cut out and followed through the clip, ready for editing, graphics and effects.
    \n
    SegmentationTrackingEditing
    \n
    \n
    \n
    \n
    \n\n
    \nHow we work\n
    From pilot to production
    \n
    \n
    \n
    01
    \n
    Connect your library
    \n
    We integrate with your MAM, storage or live feeds and define the metadata your teams actually need.
    \n
    \n
    \n
    02
    \n
    Tailor the models
    \n
    We adapt detection and VLM pipelines to your content, brands, formats and editorial taxonomy.
    \n
    \n
    \n
    03
    \n
    Scale in production
    \n
    Pipelines run in the cloud or on premises, writing metadata back into your MAM, with ongoing quality monitoring.
    \n
    \n
    \n
    \n\n
    \n
    \n
    \n
    \n
    Unlock your content library
    \n
    Talk to our team about making your video and image archive searchable.
    \n
    \n
    Get startedRequest a demo
    \n
    \n
    \n
    \n\n
    \n Back to all solutions\n\n
    \n
    Smart Retail
    \n
    \n
    Gekko Labs turns in-store cameras into a real-time view of shelves, queues and customer flow. Our models help retailers keep products available, understand how stores are used and reduce loss, without changing how customers shop.
    \n
    Get startedRequest a demo
    \n
    \n
    \n
    \n
    \n\n
    \nRetail\nLive demoShelf & Shopper Analytics\n\n
    \n
    \n
    \n
    \n
    \n
    Audit a shelf in seconds
    \n
    Pick a shelf. Our model detects every facing, groups identical products without any catalogue, and flags empty gaps and items placed in the wrong block. Drag the divider to compare.
    \n
    \n
    \nGet started\nRequest a demo\n
    \n
    \n
    \n
    \n
    \n
    \n
    \"Shelf
    \"Shelf
    Input
    \n
    \n\n
    \n
    \n
    Planogram compliance
    –
    Facings detected
    –
    Product types
    –
    Empty gaps
    –
    Misplaced items
    –
    Product groupEmpty gapMisplaced item
    \n
    JSON output
    \n
    \n
    \n
    \n
    Run inferenceRunning…Run againReady. Pick an example and press Run inference.Inference completemeasuredInputResultLoading model weightsDetecting every product facingGrouping products by visual similarityChecking gaps and planogram rulesGekko shelf model
    \n
    \n\n
    \n
    \nRetail\n
    Store teams cannot see everything
    \n
    Retailers run many stores with thin margins and limited staff on the floor. Out-of-stocks, long queues and display errors cost sales but are often noticed too late. Manual audits are periodic and inconsistent across locations.
    \n
      \n
    • Shelf availability. Detect empty shelves and misplaced products so staff can restock faster.
      • \n
    • Footfall and queues. Measure traffic and queue lengths to staff checkouts and floors effectively.
      • \n
    • Planogram compliance. Check displays, pricing and promotions match the plan across every store.
      • \n
    • Loss prevention. Highlight unusual checkout and shelf activity for review by your team.
      • \n
    \n
    \n
    \n\"Checkout\nCheckout Dwell Time\n
    \n
    \n\n
    \n
    \n
    Use cases
    Vision AI in action
    \n
    \n
    \n
    \n
    \n\"Footfall\n
    \n
    \n
    Footfall Heatmaps
    \n
    Customer movement is aggregated over time into a heatmap that reveals hot zones and dead aisles at a glance. Optimise store layouts, product placement and staffing with real behavioural data.
    \n
    Object TrackingHeatmapsStore Analytics
    \n
    \n
    \n
    \n
    \n\"Queue\n
    \n
    \n
    Queue Management
    \n
    People waiting in line are detected and counted in real time inside a defined region. Staff are alerted to open more tills before queues build, improving service and reducing walk-outs.
    \n
    Object DetectionRegion CountingQueue Analytics
    \n
    \n
    \n
    \n
    \n\n
    \nHow we work\n
    From pilot to production
    \n
    \n
    \n
    01
    \n
    Use existing cameras
    \n
    We connect to your in-store CCTV and add shelf cameras only where they add clear value.
    \n
    \n
    \n
    02
    \n
    Train on your stores
    \n
    We fine-tune models on your products, fixtures and store layouts, with privacy-preserving processing.
    \n
    \n
    \n
    03
    \n
    Deploy and act
    \n
    Models run on in-store edge devices or cloud and send alerts and insights to staff apps, BI tools or your retail systems.
    \n
    \n
    \n
    \n\n
    \n
    \n
    \n
    \n
    See your stores in real time
    \n
    Talk to our team about a pilot in a few of your locations.
    \n
    \n
    Get startedRequest a demo
    \n
    \n
    \n
    \n\n
    \n Back to all solutions\n\n
    \n
    Vision-Guided Robotics
    \n
    \n
    Gekko Labs builds the perception layer that lets robots see, understand and act in the real world. Our compact detection, segmentation and VLM models run on embedded hardware, giving robots reliable object recognition and scene understanding in changing environments.
    \n
    Get startedRequest a demo
    \n
    \n
    \n
    \n
    \n\n
    \nRobotics\nLive demoRobotic Cell Perception\n\n
    \n
    \n
    \n
    \n
    \n
    Tell the robot what to pick
    \n
    Choose a scene and an instruction. Our vision model finds the object from plain language, cuts it out at pixel level, estimates depth from a single camera and plans where the gripper should close. Then explore the scene in 3D.
    \n
    \n
    \nGet started\nRequest a demo\n
    \n
    \n
    \n
    \n
    Instruction to the robot
    \n
    \n
    \"RobotDrag to rotate · scroll to zoom
    Input
    \n
    \n\n
    \n
    \n
    Detection confidence
    –
    Gripper angle
    –
    Grasp width
    –
    Relative depth
    –
    Object pixels
    –
    Inference time
    –
    \n
    JSON output
    \n
    \n
    \n
    \n
    Run inferenceRunning…Run againReady. Pick an example and press Run inference.Inference completemeasuredInputResultLoading model weightsEstimating depth from a single cameraFinding the object from the instructionSegmenting the object at pixel levelPlanning a stable graspBuilding the 3D sceneGekko robotics vision model
    \n
    \n\n
    \n
    \nRobotics\n
    Real environments are messy
    \n
    Robots that work well in the lab often struggle with new objects, clutter and changing light in real facilities. Off-the-shelf models rarely match the exact items and conditions a robot faces. Perception failures lead to missed picks, stoppages and lost trust in automation.
    \n
      \n
    • Robust perception. Detect and segment objects reliably under varying lighting, clutter and viewpoints.
      • \n
    • Grasp and pick support. Precise object masks and poses help arms pick varied items accurately.
      • \n
    • Embedded efficiency. Models optimised for Jetson-class and other edge hardware with tight power budgets.
      • \n
    • Scene understanding. VLMs let robots interpret instructions and context, not just bounding boxes.
      • \n
    \n
    \n
    \n\"Vision-Guided\nVision-Guided Pick & Place\n
    \n
    \n\n
    \n
    \n
    Use cases
    Vision AI in action
    \n
    \n
    \n
    \n
    \n\"6-DoF\n
    \n
    \n
    6-DoF Object Pose
    \n
    The full 3D position and orientation of everyday items is estimated from camera images. Grippers know exactly where and how to grasp, enabling flexible bin picking and assembly.
    \n
    6-DoF Pose3D VisionGrasp Planning
    \n
    \n
    \n
    \n
    \n\"Vision-Guided\n
    \n
    \n
    Vision-Guided Arm
    \n
    Live detection guides a robot arm to pick parts and reject the defective ones.
    \n
    RoboticsDetection
    \n
    \n
    \n
    \n
    \n\n
    \nHow we work\n
    From pilot to production
    \n
    \n
    \n
    01
    \n
    Capture robot data
    \n
    We collect imagery from your robot's own cameras and sensors in the environments where it operates.
    \n
    \n
    \n
    02
    \n
    Train and optimise
    \n
    We train perception models on your objects and tasks, then compress and optimise them for your onboard compute.
    \n
    \n
    \n
    03
    \n
    Integrate and iterate
    \n
    We integrate with your ROS or control stack and keep improving models as new objects and edge cases appear.
    \n
    \n
    \n
    \n\n
    \n
    \n
    \n
    \n
    Give your robots better vision
    \n
    Talk to our team about the perception challenge holding your robots back.
    \n
    \n
    Get startedRequest a demo
    \n
    \n
    \n
    \n\n
    \n Back to all solutions\n\n
    \n
    Intelligent Transportation
    \n
    \n
    Gekko Labs applies computer vision to roads, rail and public transport networks. Our models monitor traffic, detect incidents and inspect infrastructure using existing cameras, giving operators the real-time awareness they need to keep people moving safely.
    \n
    Get startedRequest a demo
    \n
    \n
    \n
    \n
    \n\n
    \nTransportation\nLive demoIntersection Flow Analysis\n\n
    \n
    \n
    \n
    \n
    \n
    Turn a traffic camera into live statistics
    \n
    Press Run inference on this aerial clip. Our model detects every vehicle, follows it across frames, estimates its speed and builds the traffic dashboard as the video plays.
    \n
    \n
    \nGet started\nRequest a demo\n
    \n
    \n
    \n
    \n
    \n
    \n
    Input
    \n
    \n\n
    \n
    \n
    Vehicles counted
    –
    In view now
    –
    Heading right →
    –
    Heading left ←
    –
    Average speed
    –
    Top speed
    –
    Vehicle mix
    Cars
    0
    Vans
    0
    Trucks
    0
    Live events
      \n
      JSON output
      \n
      \n
      \n
      \n
      Run inferenceRunning…Run againReady. Pick an example and press Run inference.Inference completemeasuredInputResultLoading model weightsDecoding the video streamDetecting vehicles in every frameTracking each vehicle and measuring speedCounting by direction, lane and vehicle typeGekko traffic modelframescarvantrucklane
      \n
      \n\n
      \n
      \nTransportation\n
      Huge networks, few eyes
      \n
      Transport operators manage thousands of cameras and kilometres of infrastructure with small control-room teams. Incidents are often reported late, and inspections are slow and periodic. Delays in detection mean congestion, safety risks and higher maintenance costs.
      \n
        \n
      • Traffic analytics. Count and classify vehicles, cyclists and pedestrians to understand real traffic patterns.
        • \n
      • Incident detection. Spot stopped vehicles, debris and wrong-way driving as soon as they happen.
        • \n
      • Infrastructure inspection. Detect cracks, potholes and track defects from vehicle-mounted or fixed cameras.
        • \n
      • Passenger flow. Measure crowding at stations and stops to plan capacity and services.
        • \n
      \n
      \n
      \n\"Highway\nHighway Vehicle Tracking\n
      \n
      \n\n
      \n
      \n
      Use cases
      Vision AI in action
      \n
      \n
      \n
      \n
      \n\"Parking\n
      \n
      \n
      Parking Management
      \n
      Each parking bay is classified as free or occupied from a single overhead camera, with live totals on screen. Guide drivers to open spaces and understand occupancy patterns without in-ground sensors.
      \n
      Object DetectionParking AnalyticsSmart City
      \n
      \n
      \n
      \n
      \n\"Speed\n
      \n
      \n
      Speed Estimation
      \n
      The speed of every vehicle is estimated from a single fixed camera.
      \n
      TrackingSpeed
      \n
      \n
      \n
      \n
      \n\"Road\n
      \n
      \n
      Road Crack Detection
      \n
      Cracks in roads, bridges and walls are segmented at pixel level so maintenance crews can prioritise repairs.
      \n
      SegmentationInfrastructure
      \n
      \n
      \n
      \n
      \n\"Aerial\n
      \n
      \n
      Aerial Surveillance
      \n
      Hundreds of small vehicles are detected in high-altitude drone footage of busy interchanges.
      \n
      AerialSmall ObjectsTraffic
      \n
      \n
      \n
      \n
      \n\n
      \nHow we work\n
      From pilot to production
      \n
      \n
      \n
      01
      \n
      Connect network cameras
      \n
      We integrate with your existing traffic, station and vehicle-mounted cameras through your VMS or video streams.
      \n
      \n
      \n
      02
      \n
      Tune for your network
      \n
      We train detection and segmentation models on your roads, vehicles, weather and lighting conditions.
      \n
      \n
      \n
      03
      \n
      Deploy and alert
      \n
      Models run at the roadside edge or in the cloud and push events to your traffic management or maintenance systems, with ongoing support.
      \n
      \n
      \n
      \n\n
      \n
      \n
      \n
      \n
      Get real-time network awareness
      \n
      Talk to our team about bringing vision AI to your transport network.
      \n
      \n
      Get startedRequest a demo
      \n
      \n
      \n
      \n\n
      \n Back to all solutions\n\n
      \n
      Smart Warehousing & Logistics
      \n
      \n
      Gekko Labs helps warehouses and fulfilment centres see their operations in real time. Our models count stock, read labels, verify packages and monitor safety across docks and aisles, feeding accurate data straight into your warehouse systems.
      \n
      Get startedRequest a demo
      \n
      \n
      \n
      \n
      \n\n
      \nWarehousing\nLive demoConveyor Package Detection\n\n
      \n
      \n
      \n
      \n
      \n
      Stop forklift near-misses before they happen
      \n
      Press Run inference on a warehouse camera. Our model detects people and forklifts, follows them, draws a danger zone around every moving forklift and raises an alert the moment someone steps inside.
      \n
      \n
      \nGet started\nRequest a demo\n
      \n
      \n
      \n
      \n
      \n
      \n
      Input
      \n
      \n\n
      \n
      \n
      People in view
      –
      Forklifts in view
      –
      People in danger zone
      –
      Proximity alerts
      –
      Incident log
        \n
        JSON output
        \n
        \n
        \n
        \n
        Run inferenceRunning…Run againReady. Pick an example and press Run inference.Inference completemeasuredInputResultLoading model weightsDecoding the camera streamDetecting people and forklifts in every frameTracking and checking danger zonesframesPersonentered forklift zonealertsGekko industrial safety model
        \n
        \n\n
        \n
        \nWarehousing\n
        Fast flows, error-prone checks
        \n
        Warehouses handle growing volumes with tight delivery windows and labour shortages. Manual counts, scans and damage checks are slow and easy to get wrong. Inventory errors and accidents ripple into missed orders, claims and downtime.
        \n
          \n
        • Inventory visibility. Count pallets and cartons and detect empty or misplaced locations automatically.
          • \n
        • Label and parcel reading. Read labels and check parcel condition at inbound and outbound docks.
          • \n
        • Safer aisles. Detect people near moving equipment and flag unsafe behaviour in real time.
          • \n
        • Faster dock operations. Track loading progress and dock usage to reduce waiting and handling time.
          • \n
        \n
        \n
        \n\"Parcel\nParcel Detection\n
        \n
        \n\n
        \n
        \n
        Use cases
        Vision AI in action
        \n
        \n
        \n
        \n
        \n\"Human-Aware\n
        \n
        \n
        Human-Aware AMR Mapping
        \n
        A mobile robot builds a live 3D map of warehouse aisles while segmenting people, so it can plan routes that keep a safe distance. Safer autonomy in spaces shared with workers.
        \n
        3D MappingPeople SegmentationAutonomous Robots
        \n
        \n
        \n
        \n
        \n\"Automated\n
        \n
        \n
        Automated Package Counting
        \n
        Parcels are tracked and counted as they cross a virtual line on the conveyor, with IN/OUT totals updated live. Reconcile shipments automatically and spot throughput drops instantly.
        \n
        Object TrackingObject CountingThroughput Analytics
        \n
        \n
        \n
        \n
        \n\n
        \nHow we work\n
        From pilot to production
        \n
        \n
        \n
        01
        \n
        Connect warehouse cameras
        \n
        We use your existing CCTV and scanners, adding cameras at key docks and stations where needed.
        \n
        \n
        \n
        02
        \n
        Train on your goods
        \n
        We fine-tune models on your packaging, labels, racking and equipment for reliable results in your facility.
        \n
        \n
        \n
        03
        \n
        Integrate with your WMS
        \n
        Models run on edge or cloud and sync events with your WMS and dashboards, with monitoring and continuous improvement.
        \n
        \n
        \n
        \n\n
        \n
        \n
        \n
        \n
        Make your warehouse visible
        \n
        Talk to our team about a pilot at one of your docks or sites.
        \n
        \n
        Get startedRequest a demo
        \n
        \n
        \n
        \n\n
        \n Back to all solutions\n\n
        \n
        Security & Surveillance
        \n
        \n
        Gekko Labs turns security cameras into an intelligent detection layer. Our models recognise intrusions, loitering, unattended objects and unsafe activity in real time, so operators focus on genuine events instead of watching endless video walls.
        \n
        Get startedRequest a demo
        \n
        \n
        \n
        \n
        \n\n
        \nSecurity\nLive demoLine-Crossing Counting\n\n
        \n
        \n
        \n
        \n
        \n
        Ask the camera anything
        \n
        Pick a camera and a question. Our vision-language model answers in plain words and marks the people and objects that support its answer, turning every camera into a searchable safety assistant.
        \n
        \n
        \nGet started\nRequest a demo\n
        \n
        \n
        \n
        \n
        Ask the camera
        \n
        \n
        \"CCTV\"Answer
        Input
        \n
        \n\n
        \n
        \n
        Regions cited
        –
        Inference time
        –
        \n
        JSON output
        \n
        \n
        \n
        \n
        Run inferenceRunning…Run againReady. Pick an example and press Run inference.Inference completemeasuredInputResultLoading model weightsReading the sceneReasoning about the questionLocating the evidenceGekko vision-language model
        \n
        \n\n
        \n
        \nSecurity\n
        Too many screens, too few operators
        \n
        Security teams monitor large numbers of cameras, and attention drops quickly when watching video for hours. Basic motion detection floods operators with false alarms from weather, animals and lighting. Real threats can be missed or found only after the fact.
        \n
          \n
        • Perimeter protection. Detect people and vehicles crossing boundaries, day or night, with fewer false alarms.
          • \n
        • Real-time alerts. Send relevant events with video clips straight to operators and response teams.
          • \n
        • Works with existing CCTV. Add intelligence to the cameras and VMS you already run.
          • \n
        • Fast forensic search. Find people, vehicles or events across hours of footage in seconds.
          • \n
        \n
        \n
        \n\"Crowd\nCrowd Tracking\n
        \n
        \n\n
        \n
        \n
        Use cases
        Vision AI in action
        \n
        \n
        \n
        \n
        \n\"PPE\n
        \n
        \n
        PPE Compliance
        \n
        Hard hats and vests are verified on every worker to enforce site safety.
        \n
        DetectionSafety
        \n
        \n
        \n
        \n
        \n\"Crowd\n
        \n
        \n
        Crowd Zone Counting
        \n
        People are counted per zone in dense crowds to manage capacity and safety.
        \n
        TrackingCounting
        \n
        \n
        \n
        \n
        \n\"Smoke\n
        \n
        \n
        Smoke Detection
        \n
        Smoke is detected early to raise fire alarms before flames spread.
        \n
        SegmentationSafety
        \n
        \n
        \n
        \n
        \n\n
        \nHow we work\n
        From pilot to production
        \n
        \n
        \n
        01
        \n
        Connect your VMS
        \n
        We integrate with your existing cameras and video management system through standard streams and APIs.
        \n
        \n
        \n
        02
        \n
        Tune to your sites
        \n
        We adapt detection models to your perimeters, zones and rules to cut false alarms.
        \n
        \n
        \n
        03
        \n
        Deploy and refine
        \n
        Models run on edge appliances or in the cloud, sending alerts to your VMS or control room, with ongoing tuning and support.
        \n
        \n
        \n
        \n\n
        \n
        \n
        \n
        \n
        Upgrade your security operations
        \n
        Talk to our team about adding real-time vision AI to your existing cameras.
        \n
        \n
        Get startedRequest a demo
        \n
        \n
        \n
        \n\n
        \n
        \n"}