For Academies, Scouts, and Tech Founders. We build custom Computer Vision Engines that track pitch velocity, spin rate, and batting mechanics in real-time—without radar guns or wearable sensors.
Modern baseball is obsessed with data, but relying on TrackMan or Rapsodo limits your market. Whether you are building a B2C coaching app or a scouting platform, hardware dependency creates three blockers.
You can't scale an app if every user needs a $2,000 device. Our Vision-Based AI extracts pro-grade metrics from a standard iPhone camera.
Radar tracks the ball, not the body. It can't tell you why a pitcher lost velocity. Our AI tracks Skeletal Kinematics (shoulder separation, stride length) to identify mechanical flaws.
Scouts can't be everywhere. Our centralized engine processes video from thousands of high school games automatically, flagging prospects with "90mph+ potential.
Hardware data lives in silos, limiting collaboration, scalability, and unified performance insights across teams and environments.
From "Sandlot to Stadium"—scalable tech for every level.
For B2C apps. Users record a bullpen session, and our on-device model calculates Release Point, Velocity, and Arm Slot consistency instantly, offering drill recommendations.
For agencies and colleges. Our engine ingests game footage to auto-grade players on the "20-80 Scale" based on running speed (60-yard dash time calculated from video) and exit velocity estimation.
For hitting academies. We track key hitting metrics—Bat Speed, Attack Angle, and Hip Rotation—using just a side-view camera, replacing expensive 3D motion capture labs.
A fastball takes 400ms to reach the plate. We process 120fps video (standard on modern phones) to capture the ball's flight path with granular precision.
We convert 2D video into a 3D skeletal model. This allows us to measure "Hip-to-Shoulder Separation" (the key to velocity) even from a non-perfect camera angle.
By calibrating the mound distance (60ft 6in), our physics engine calculates velocity and break. We use "Spin Decay" logic to estimate Spin Rate (RPM) purely from trajectory curvature.
Our logic layer classifies the pitch type (Fastball, Slider, Curve) based on velocity and movement profile, tagging the video automatically.
Folio3 AI has built an advanced video analysis solution using pose estimation and biomechanics tracking to evaluate athlete performance, improve technique, and minimize injury risks. Key Outcomes Improved player performance through detailed motion and technique analysis. Reduced injury risk by identifying biomechanical inefficiencies early. Delivered real-time visual feedback for faster coaching and correction. Enabled data-driven training decisions with actionable performance insights.
Turn any game video into pro-level insights, identify mechanics, track performance, and discover hidden talent, with no expensive hardware required at scale.
Fill the form below or Contact us at +1 408 365-4638 / email us via contact@folio3.ai
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+1 408 365-4638
contact@folio3.ai
6701 Koll Center Parkway, #250 Pleasanton, CA 94566
