Available for Consultation
Available for Consultation
Available for Consultation
Our Work
In Action
Featured
Work
Metric Hive engineers custom Computer Vision and Edge AI agents that detect defects, track assets, and automate safety with >99% precision.
(Portfolio)
Recent Works
A production-ready tracking system built for the toughest conditions in computer vision: high-speed play, heavy motion blur, and aggressive camera pans.
01
/ 03
Ice Hockey Player Tracking
Status
Production-Ready
Tech Stack
Custom CV Pipeline
Features
Camera Stabilization
Mask Propagation
Jersey Recognition
Multi-Object Tracking (MOT)
A production-ready tracking system built for the toughest conditions in computer vision: high-speed play, heavy motion blur, and aggressive camera pans.
01
/ 03
Ice Hockey Player Tracking
Status
Production-Ready
Tech Stack
Custom CV Pipeline
Features
Camera Stabilization
Mask Propagation
Jersey Recognition
Multi-Object Tracking (MOT)
A production-ready tracking system built for the toughest conditions in computer vision: high-speed play, heavy motion blur, and aggressive camera pans.
01
/ 03
Ice Hockey Player Tracking
Status
Production-Ready
Tech Stack
Custom CV Pipeline
Features
Camera Stabilization
Mask Propagation
Jersey Recognition
Multi-Object Tracking (MOT)
An R&D deep dive into Meta's SAM 3D release. We tested the new "Concept-Centric" architecture on high-complexity American Football scenes to evaluate the distinctions between static scene generation and dynamic body rigging.
02
/ 03
Player 3D Pose R&D
Status
R&D / Prototype
Focus
3D Reconstruction
Features
3D Computer Vision
Biomechanics
Flow Matching
Momentum Human Rig (MHR)
An R&D deep dive into Meta's SAM 3D release. We tested the new "Concept-Centric" architecture on high-complexity American Football scenes to evaluate the distinctions between static scene generation and dynamic body rigging.
02
/ 03
Player 3D Pose R&D
Status
R&D / Prototype
Focus
3D Reconstruction
Features
3D Computer Vision
Biomechanics
Flow Matching
Momentum Human Rig (MHR)
An R&D deep dive into Meta's SAM 3D release. We tested the new "Concept-Centric" architecture on high-complexity American Football scenes to evaluate the distinctions between static scene generation and dynamic body rigging.
02
/ 03
Player 3D Pose R&D
Status
R&D / Prototype
Focus
3D Reconstruction
Features
3D Computer Vision
Biomechanics
Flow Matching
Momentum Human Rig (MHR)
A seamless fusion of sports analytics and AI. This system acts as a "digital referee," utilizing custom optimized models to track the ball, players, and game events in real-time on midrange hardware.
03
/ 03
Padel Game Analysis
Status
Production-Ready
Tech Stack
End-to-End CV Pipeline
Features
TrackNetV3
RTMO (Pose Estimation)
Handedness Detection
Shot Detection
A seamless fusion of sports analytics and AI. This system acts as a "digital referee," utilizing custom optimized models to track the ball, players, and game events in real-time on midrange hardware.
03
/ 03
Padel Game Analysis
Status
Production-Ready
Tech Stack
End-to-End CV Pipeline
Features
TrackNetV3
RTMO (Pose Estimation)
Handedness Detection
Shot Detection
A seamless fusion of sports analytics and AI. This system acts as a "digital referee," utilizing custom optimized models to track the ball, players, and game events in real-time on midrange hardware.
03
/ 03
Padel Game Analysis
Status
Production-Ready
Tech Stack
End-to-End CV Pipeline
Features
TrackNetV3
RTMO (Pose Estimation)
Handedness Detection
Shot Detection
(FAQs)
Your Questions, Answered
Helping you understand how we mitigate risk and deploy Edge AI.
Why Metric Hive vs. an in-house Engineer?
How does the process work?
We work in rigid 2-week sprints. It starts with a 5-Day Feasibility Audit (Go/No-Go check). If viable, we move to a 4-Week Pilot to prove the model on your hardware. Finally, we execute Production Deployment with full integration.
Do I need a massive dataset to start?
What hardware do you support?
What if the model isn't accurate enough?
Who owns the Intellectual Property (IP)?
(FAQs)
Your Questions, Answered
Helping you understand how we mitigate risk and deploy Edge AI.
Why Metric Hive vs. an in-house Engineer?
How does the process work?
We work in rigid 2-week sprints. It starts with a 5-Day Feasibility Audit (Go/No-Go check). If viable, we move to a 4-Week Pilot to prove the model on your hardware. Finally, we execute Production Deployment with full integration.
Do I need a massive dataset to start?
What hardware do you support?
What if the model isn't accurate enough?
Who owns the Intellectual Property (IP)?
(FAQs)
Your Questions, Answered
Helping you understand how we mitigate risk and deploy Edge AI.
Why Metric Hive vs. an in-house Engineer?
How does the process work?
We work in rigid 2-week sprints. It starts with a 5-Day Feasibility Audit (Go/No-Go check). If viable, we move to a 4-Week Pilot to prove the model on your hardware. Finally, we execute Production Deployment with full integration.
Do I need a massive dataset to start?
What hardware do you support?
What if the model isn't accurate enough?
Who owns the Intellectual Property (IP)?
Let's Connect
Let's Connect
Let's Connect