AI Gait Analysis Software Built Into Your Product, Not Sold as Someone Else's App
Folio3 builds custom AI gait analysis software and markerless motion capture systems for health tech, sports, and retail products, turning footage into calibrated biomechanical data your team owns.
Folio3 AI Gait Analysis SoftwareNo belts, mats, or rigs
What a custom-built gait analysis system delivers
Instead of a fixed dashboard, a custom system gives your product these four capabilities from day one, and lets you extend every one of them after launch.
Markerless capture
Runs from a single smartphone or fixed camera. No belts, mats, or marker rigs.
Calibrated metrics
Real-world step length, cadence, and joint angles, not raw pixel estimates.
Extensible model
Add new metrics after launch instead of waiting on a vendor roadmap.
Embedded integration
APIs and SDKs built for your app, EHR, or wearable, not a standalone tool.
Our AI gait analysis software solution: what we build
Six components work together to turn raw video into the calibrated gait analysis technology your product runs on.
Markerless motion capture engine
Pose estimation tuned to lower-body landmarks, so there is no need for reflective markers or specialized cameras.
Gait cycle segmentation logic
Automatic detection of stance and swing phases straight from raw video. This is the foundation every other metric is built on.
Spatial and temporal calibration
Converts pixel movement into real step length, cadence, and velocity, calibrated to the actual scene rather than a generic assumption.
Asymmetry and deviation detection
Compares left and right sides of the body to flag compensation patterns that can point to injury risk or inefficient movement.
Clinical and coaching reporting layer
Client-ready, brandable reports and dashboards in the format your users actually need.
Product integration layer
APIs and SDKs built to embed the whole system into your existing app, EHR, or wearable device. Gait analysis becomes a feature of your product, not a separate tool.
What an AI gait analysis system can measure
A custom-built gait analysis system covers four categories of metric, each configurable to your population and use case.
Spatial metrics
Step length, stride length, step width, and foot placement, calibrated to the real scene.
Temporal metrics
Cadence, ground contact time, stance versus swing duration, and full gait cycle timing.
Kinematic metrics
Hip, knee, and ankle joint angles, range of motion, and angular velocity.
Clinical indicators
Pronation and supination, symmetry index, compensation patterns, and stability indicators.
Why off-the-shelf gait analysis tools hit a ceiling
Teams evaluating gait analysis technology usually choose between a markerless app, a wearable sensor platform, or a lab-grade mocap rig. All three come with a catch.
Fixed metric set
Off-the-shelf tools lock you to the vendor's own algorithm, so metrics can't be added or customized.
No data or IP ownership
Even white-labeled apps keep the model and the patient or athlete data on the vendor's platform.
Hardware or sensor lock-in
Sensor belts, treadmills, or mocap rigs limit where and how testing can happen.
Generic accuracy claims
Consumer and clinical tools are tuned for their own population, not necessarily yours.
Built around your product, not a vendor's
Markerless apps, sensor platforms, and lab mocap each lock you into someone else's hardware or output. A custom-built system uses three layers instead, pose estimation, motion logic, and clinical output, engineered around your product.
Video in, biomechanical data out
Joint angles, stance and swing phases, and calibrated distances, all from a single camera feed.
| Custom-built (Folio3) | Markerless app | Sensor platform | Lab-grade 3D mocap | |
|---|---|---|---|---|
| Hardware required | None | None | Sensor belt | Multi-camera rig |
| Data and IP ownership | Yours | Vendor's | Vendor's | Vendor's |
| Cost model | One-time build, ongoing tuning | Per-scan or subscription | Subscription plus hardware | Hardware purchase plus subscription |
The AI gait analysis technology stack we work with
Production-ready gait analysis technology combines computer vision frameworks, biomechanics logic, and infrastructure built for your deployment environment.
Pose estimation
- OpenPose
- MediaPipe
- Custom-trained architectures
Computer vision
- Markerless video capture
- Single and multi-camera calibration
Biomechanics logic
- Gait cycle segmentation
- Joint angle calculation
- Symmetry scoring
Data and integration
- REST APIs and SDKs
- EHR and wearable data pipelines
Cloud and deployment
- AWS, Azure, GCP
- On-device and edge inference
Reporting
- Configurable dashboards
- Exportable clinical and coaching reports
How we build your gait analysis software
A five-step process connects discovery, model training, calibration, and integration into one structured engagement, followed by ongoing tuning.
Discovery and use case definition
Population, camera setup, accuracy targets, and integration points get defined before any model work starts.
Markerless pose estimation
Models get trained on 33 or more anatomical landmarks with a lower-body focus.
Gait cycle segmentation
Stance and swing phase logic gets built for your target population's actual movement patterns.
Calibration and accuracy validation
Scene calibration and real-world distance and speed testing confirm the system's measurements against known benchmarks before deployment.
Deployment and integration
The system gets embedded into your app, portal, or clinical workflow, with ongoing support and model tuning after launch.
Engagement models for this solution
Choose an engagement model based on your existing data, target population, and how much of the system needs to be validated before a full rollout.
Proof of concept
4 to 6 weeks to validate feasibility, model accuracy, and technical risk on your target population.
MVP build
3 to 5 months to build a working system covering your core metric set and a first integration point.
Full product integration
5 to 9 months to embed the system across your app, portal, or clinical workflow.
Ongoing model tuning and support
Continued accuracy monitoring and metric additions as your product and population evolve.
Running gait analysis software for sports and performance
Coaches get heel strike detection, overstriding flags, and cadence inefficiency tracking straight from training footage.
Real-time or post-run feedback
Feedback comes back in real time or right after a session, inside your own coaching or team app. No extra lab time on an athlete's schedule.
Season-long gait tracking
Track gait changes across a full season and get a running record of how someone's form actually changes, not a single appointment snapshot.
Heel strike and overstriding flags
Detect heel strike patterns, overstriding, and cadence inefficiencies directly from training footage.
The business case for AI-based gait analysis
A markerless app or sensor subscription looks cheaper in year one, but the ceiling on what a vendor's model will do for your population stays the same.
Per-scan and subscription costs keep running
A markerless app or sensor subscription charges per scan or seat, and that cost never stops.
Sensor and hardware costs limit where you test
Wearable platforms need a physical device on hand every session, capping where testing can happen.
Lab mocap confines you to one location
Lab-based 3D motion capture solves accuracy but not scale. Hardware cost and setup keep it to one room.
A custom build shifts the economics
The cost moves from a recurring vendor fee to a one-time build, with a model that keeps improving for your use case.
AI gait analysis solutions across industries
The same underlying system adapts to five different operating environments, each with its own metric priorities.
Clinical rehabilitation and physiotherapy
Range of motion tracking, stride symmetry, and post-operative progress monitoring, built into existing PT or rehab software.
Sports performance and coaching apps
Running form analysis and injury-risk pattern detection embedded directly into a coaching platform.
Retail footwear and orthotics
In-store or at-home pronation and supination assessment that feeds into product recommendations at the point of sale.
Digital health platforms
Smartphone-based gait screening deployed at scale across a patient or user base.
Wearable and sensor companies
Video-based validation layered on top of existing sensor data, useful for confirming what the sensors are already reporting.
Built for regulated and clinical workflows
The system is HIPAA compliant, with data handling and audit trail decisions made for clinical workflows from the start, not retrofitted after.
Data handling
Audit trails
Access control
Model ownership
HIPAA compliant
Patient and athlete data stays under access control and audit trails built for regulated healthcare workflows.
Your infrastructure
Deployed inside your cloud environment or on-device, not a shared multi-tenant platform.
Data ownership, by design
The model, the code, and any patient or athlete data stay with your product, not with Folio3, inside a HIPAA-compliant architecture.
Data handling
Built around HIPAA and clinical data requirements.
Audit trails
Supports traceability for regulated deployments.
Model ownership
You hold the model and can retrain it independently.
Meet the team behind this build
Folio3's gait analysis work is led by specialists spanning computer vision engineering and sports industry go-to-market, from model training to deployment planning for sports and health tech products.
Abdul Sami
Head of AI and Machine Learning, Senior Software Architect, Folio3 AIAbdul leads the engineering behind Folio3's computer vision and biomechanics systems, including markerless pose estimation and calibrated motion capture. With 20+ years in AI and software architecture, he builds production-ready systems, not pilots that never ship.
Rob Terry
Director of Sports Sales, North America, Folio3 AIRob leads Folio3 AI's sports sales initiatives, helping sports and health tech organizations adopt AI-driven solutions for analytics and measurable growth. He scopes the right engagement model for teams evaluating a gait analysis build.
- DiscoveryStadium rigs and smartphone tripods both had to work.
- Model buildCalibration, skill scoring, goalkeeper module, pose tracking.
- IntegrationVideo converted to JSON via API for evaluation.
Replacing GPS vests with a single camera feed
This gait analysis solution shares its computer vision foundation with Folio3's broader sports AI work. For a national football association, Folio3 replaced GPS vests and sensor balls with markerless tracking that runs from stadium rigs or a smartphone tripod, scoring player and goalkeeper performance across tactical drills.
- Single-frame calibration maps the field from any camera angle
- Dedicated goalkeeper module for reflexes and distribution accuracy
- Pose-estimation pipeline scores technique from raw footage
Why health tech, sports, and retail teams build their gait analysis system with Folio3
Six reasons product and engineering leads choose a custom build over a rented gait analysis app.
Custom-built, not white-labeled
The system gets engineered around your product, not licensed as a rebranded app.
Full IP and data ownership
The model and the data stay with you, not a third-party vendor.
Markerless, no hardware lock-in
No belts, mats, or camera rigs required to run an assessment.
Modular metrics you can extend
Add biomechanical metrics after launch instead of waiting on a vendor roadmap.
Computer vision engineering background
Pose estimation and motion logic built by a team with direct markerless capture experience.
Built for regulated and clinical workflows
Data handling and architecture decisions account for clinical and health data requirements from the start.
Explore More AI Sports Video Analysis Solutions
Gait analysis represents just one piece of our larger sports AI and movement analysis ecosystem. See how Folio3 develops tailored computer vision solutions spanning team sports, technical sports, racing, coaching, scouting, and performance-tracking workflows.
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Explore Motorsports AnalysisFrequently asked questions
What is AI gait analysis software and how does it work?
AI gait analysis software uses computer vision to convert video of a person walking or running into biomechanical data like step length, cadence, and joint angles. It works without reflective markers, using pose estimation models trained to track key points on the body.
How is a custom-built gait analysis system different from a markerless app?
A markerless app runs your data through a fixed algorithm on someone else's platform with a set list of metrics. A custom-built system is engineered around your product and your data requirements, with metrics that can be extended after launch.
How is a custom-built system different from a sensor-based platform or a 3D mocap rig?
Sensor-based platforms need a wearable device for every assessment. 3D mocap rigs need a multi-camera setup confined to one location. A custom-built markerless system needs neither, and the model and data stay under your control.
Can this replace a traditional gait lab?
For many use cases, yes. Markerless AI gait analysis reaches accuracy levels suitable for coaching, retail, and many clinical workflows. Highly specialized research applications may still call for lab-based capture.
Does the system require special hardware or a treadmill?
No. It's built to run from a single smartphone or fixed camera, no belts, mats, or marker rigs required.
Can it work with a single camera?
Yes. Single-camera setups are supported, and multi-camera configurations can be added where higher precision is needed.
Who owns the IP and the data?
You do. The model, the code, and any patient or athlete data the system generates stay with your product, not with Folio3 or a third party.
Is this built for regulated or clinical use?
Yes. The system is HIPAA compliant, with access control and audit trails built for clinical and health data workflows from the start.
Can new metrics be added after launch?
Yes. The system is built to be extended, so new spatial, temporal, kinematic, or clinical metrics can be added as your product's requirements change.
How is measurement accuracy validated?
Every build goes through scene calibration and real-world distance and speed testing against known benchmarks before deployment, confirming the output matches expected measurements for your specific camera setup and population.
How long does it take to build a gait analysis system?
A proof of concept takes 4 to 6 weeks. An MVP build takes 3 to 5 months. Full product integration takes 5 to 9 months, followed by ongoing model tuning and support.
Can it integrate with our existing app, EHR, or wearable?
Yes. The system is built with APIs and SDKs made for embedding into existing products, portals, and clinical workflows.
Ready to build a gait analysis system your product can actually own?
Off-the-shelf and white-labeled gait tools rent you a dashboard. Folio3 builds the software itself, tuned to your population and product, with the IP staying yours.
