For Leagues, Academies, and Tech Startups. We build custom Computer Vision Engines that track bowling actions, ball trajectories, and batting strokes in real-time—no expensive radar guns or wearables required.
Modern cricket requires data, but current tools are either too expensive (Hawk-Eye) or too manual. Whether you are building a coaching app or a broadcast tool, relying on legacy tech creates three blockers:
Installing radar guns and sensor mats costs thousands per pitch. Our Vision-Based AI extracts the same data from a standard smartphone or broadcast camera.
A coach "thinks" an elbow is bent. Our AI "knows" it. We measure biomechanics with < 2-degree angular precision to detect illegal actions or injury risks objectively.
Waiting for the post-match video review is too late. Our Edge-AI models deliver ball-by-ball analytics instantly, allowing coaches to adjust tactics mid-over.
The "Data Silo" Problem Ball speed lives in one tool. Biomechanics in another. Match footage in a third. Our unified AI pipeline ingests every source and outputs a single, structured performance dataset — ready for your app or API.
From "Nets to Cloud" for academies, to "Stadium to Screen" for broadcasters.
We track Release Speed, Line & Length, and Swing/Spin deviation automatically. Our "Illegal Action Detector" flags chucking (elbow extension >15 degrees) instantly.
For B2C apps. Users record a cover drive, and our on-device model analyzes the backlift, footwork, and impact point, offering pro-level coaching feedback in seconds.
Automate your media workflow. Our engine detects "Wickets," "Fours," and "Sixes" based on visual and audio cues, creating social-ready clips moments after the ball is dead.
We process video at 60-120 FPS to capture the ball even at high speeds. We support inputs from 4K broadcast cameras or standard iPhones.
We run two models simultaneously: A Ball Tracker (to calculate pitch maps and speed) and a Pose Estimator (to analyze the player's biomechanics).
Using "Monocular Depth Estimation," we turn 2D video into 3D ball paths, allowing us to predict where the ball would have hit the stumps (DRS-style).
Our logic layer classifies the outcome (e.g., "Dot Ball," "Boundary," "Wicket") and pushes the structured data to your app or API.
A sports tech startup approached Folio3 to build an affordable coaching analytics platform for academies that couldn't afford Hawk-Eye-level tools. We engineered a mobile-first computer vision pipeline delivering ball-tracking, pose estimation, and match event detection at a fraction of traditional infrastructure costs.
Whether you are building a coaching app or a broadcast tool, we have the engineering team to execute.
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+1 408 365-4638
contact@folio3.ai
6701 Koll Center Parkway, #250 Pleasanton, CA 94566
