The Motion Intelligence
Engine for
Physical AI
The Data Engine Powering Physical Intelligence
Convert raw video into physics-valid skeletal data. Instant, precise feedback on human movement.
Built for performance teams. Designed for the future of physical intelligence.
THE PROBLEM
Motion Data Is Missing From the World
Today, human movement exists mostly as raw video — unstructured, unlabeled, and unusable for machines.
Robotics systems need motion data.
Athletes need biomechanical insight.
AI needs structured physical intelligence.
But no infrastructure exists to convert real-world motion into machine-readable data.
Tenslam changes that.
Text → AI
Language Models
Required structured text corpora
Images → AI
Vision Models
Required labeled image datasets
Motion → AI
Physical Intelligence
Requires structured motion data
Technical Foundation
Powered by the NVIDIA Ecosystem
GPU Accelerated
Powered by NVIDIA Triton™ Inference Server.
Sim‑to‑Real Ready
OpenUSD Standard for NVIDIA Omniverse™.
Synthetic Data Engine
Training models with NVIDIA Isaac Sim™.
Privacy‑First
No‑Face extraction. Skeletons anonymized.
From Video to Motion Intelligence
A proprietary pipeline that transforms standard video into physics-validated data.
Smart Quality Scan
AI instantly checks lighting & blur.
Pass = Unlock Report. Fail = Free tips.
Skeletal Extraction
We discard pixels early and extract 3D skeletal graphs of joints & velocities.
Physics Validation
Motion is normalized, smoothed, and validated against biomechanical constraints.
Sim & Augmentation
Clean data is expanded through physics‑based simulation into large-scale datasets.
Actionable Output
Insights for humans today. Training data for machines tomorrow.
CORE INNOVATION
Pixel-Free Intelligence
Traditional AI analyzes pixels. Tenslam analyzes structure.
Traditional CV Pipeline
Tenslam Pipeline
Higher Speed
Skeletal graphs are orders of magnitude smaller than raw pixel tensors. Inference runs in real-time on modest hardware.
Stronger Privacy
No faces, no textures, no identifiable visual information is ever stored. Only anonymous joint coordinates persist.
Cleaner Signal
Removing appearance noise (clothing, lighting, background) isolates the biomechanical signal that actually matters for analysis.
Better Generalization
Models trained on structure transfer across environments, camera angles, and body types — unlike pixel-dependent approaches.
Motion, not appearance, is what machines need to learn.
Start Free — Scale As You Grow
From individual athletes to enterprise motion intelligence.
Free quality check before you pay.
AI Quality Check
Don't waste money on bad video.
Upload a short clip and let our AI validate it before analysis.
What you get:
- → Instant quality scan
- → Full-body detection
- → Pro-style skeleton + joint-angle HUD preview
- → One free “Golden Metric” (e.g., depth or flexion)
- → 5s Pro Template compare + 3s shareable highlight teaser
Best for: First-time users, testing camera setup
Try It Free →Pro Report
Expert movement analysis without commitment.
Fix form in days, not months.
Includes:
- → Up to 3 short clips (max 40s each)
- → Full 3D skeleton playback
- → Center of Mass (CoM) path + balance drift tracking
- → Velocity tracking for hips / bar path / key segments
- → AI voice summary of top form deviations
- → Key joint angles, timing metrics, and correction notes
Price: €9.99 per bundle
Best for: Athletes, gym users, curious beginners
Coach Mode
Track progress. Compare sessions. Coach smarter.
Designed for serious individuals and small academies.
Monthly plan includes:
- → 10 video credits per month
- → Multi-athlete dashboard (20+ athletes)
- → Asynchronous coach voice-over feedback
- → Injury risk red-flag scoring (ACL / lower back)
- → Trend analysis, comparisons, and athlete history
Price: €29.99 / month
Best for: Coaches, academies, committed athletes
Enterprise and API access available on request. Contact us →
Built for Movement-Critical Domains
Athletes
Coaches & Academies
Physiotherapists
Robotics Teams
Biomechanics Researchers
Industrial Safety
If movement matters, Tenslam helps you measure it.
How It Works
Video Ingestion
Upload raw footage from any device.
3D Skeleton Extraction
AI extracts 33+ precise keypoints.
Synthetic Variation
Our engine analyzes motion depth & physics.
Insight Generation
Instant feedback on angles & performance.
COMPOUNDING ADVANTAGE
The Motion Intelligence Flywheel
Every uploaded video improves the system. Scale creates defensibility.
More Videos
Users upload movement footage from any standard camera.
More Motion Data
Each video is decomposed into physics-validated skeletal sequences.
Better Models
Larger, more diverse datasets improve extraction accuracy and generalization.
Better Feedback
Higher-quality models produce more precise, actionable movement insights.
More Users
Better output attracts more athletes, coaches, and enterprise clients.
Over time, Tenslam becomes the largest structured human movement dataset ever created.
TECHNICAL MOAT
Defensibility
Tenslam improves with scale. Motion intelligence is a data problem. Data advantages compound.
Proprietary Biomechanical Priors
Every processed motion sequence teaches our system sport-specific joint constraints, timing patterns, and failure modes. These learned priors cannot be replicated without comparable data volume.
Data Advantages Compound
More data improves extraction accuracy, which attracts more users, which generates more data. This cycle creates an exponentially widening gap over competitors.
Physics-Validated Quality
Unlike raw pose estimation outputs, our pipeline enforces biomechanical constraints — joint limits, conservation of momentum, anatomical plausibility — producing data clean enough to train downstream models.
Our system learns from every processed motion sequence, building proprietary biomechanical priors that cannot be replicated without comparable data volume.
Privacy by Design
- 🛡️Raw video is never stored
- 👤Only anonymous motion data is processed
- 🇪🇺EU-based infrastructure
We analyze motion, not identity.
Learn more about data & privacy →SKILL AUDIT REPORT
"You don’t need more practice.
You need clearer feedback."
Example: Tennis Serve Analysis (9.2s video)
User vs Elite Reference
3D overlay showing exactly where your form deviates from pro benchmarks.
Key Technical Findings
Targeted detection: "Incomplete Hip Drive" or "Shoulder Over-rotation".
Injury Risk Snapshot
Biomechanical risk index (Shoulder, Back, Knee) to prevent long-term damage.
Actionable Corrections
Top 3 focus points for the next 2 weeks. Simple, not academic.
Why Tenslam Vision
Motion‑First, Not Vision‑First
We discard pixels early and operate on structure, timing, and physics.
Quality Over Volume
Less than a third of uploaded motion becomes stored data by design.
Technical Credibility
Founder-led engineering. Built to conform to global privacy and security standards.
Initial Revenue Focus
We generate revenue early while building long-term motion intelligence.
Every report processed feeds our Synthetic Data Engine, refining the "Physical AI" model.
Technical Foundation
[Technical Documentation – Coming Soon]
Tenslam is building the foundational dataset layer for training physical AI systems.
MARKET TIMING
Why Now
Three converging trends make motion intelligence infrastructure inevitable.
Robotics Requires Real-World Motion Data
Humanoid robotics companies (Tesla Optimus, Figure, 1X) need massive libraries of human movement to train imitation-learning policies. Synthetic-only data lacks the distributional richness of real motion.
Simulation Needs Real Movement Priors
Physics engines like NVIDIA Isaac Sim generate synthetic trajectories, but they need real-world motion priors to produce plausible distributions. Without ground-truth seeds, sim-to-real transfer fails.
Cameras Everywhere, Motion Data Nowhere
The world generates billions of hours of movement video annually. Almost none of it is structured into machine-readable motion data. The capture hardware exists — the extraction layer doesn't.
The world is generating movement faster than anyone can structure it.
Tenslam is the first system designed to capture it at scale.