Kinetic OS builds the hardware-agnostic AI subsurface digital twin for railway trackbed assessment and predictive maintenance.

🤖 Real-Data AI
Autonomous Res-SAM (reservoir computing + SAM adapters) detects ballast fouling, moisture, voids, and layer interfaces directly from real GPR acquisitions. No synthetic data. No legacy academic toolchains.

🦾 Hardware Agnostic
Ingests raw .dzt/.rd3 from any GPR manufacturer. Your existing antennas and fleets become dramatically more valuable with zero proprietary lock-in.

💰 Economic Oracle
We turn subsurface data into financial proof. On a real 8.5 km commuter corridor, legacy blanket ballast replacement was budgeted at $18 M. Our targeted approach showed only 38 % required intervention, dropping the cost to $7 M — $11 M in immediate CapEx savings.

⚡ Real-Time + Edge
Continuous Pulse mode (every train a sensor) + NVIDIA Jetson Orin Nano edge inference (TensorRT, sub-10 ms) feeds live 3D digital twins, copilot, and verified anomalies into Supabase. What used to take expert analysts days now happens in hours.

We combine gprpy processing, real annotation workflows, Python/FastAPI, Next.js + Plotly 3D dashboards, and production-grade edge deployment to eliminate the human and software bottlenecks that define ENSCO, IDS GeoRadar, and traditional consultancies.

Pilot-ready. Built for asset managers and track engineers who need clear CapEx decisions, not more raw data.

Kinetic. GPR Intelligence

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Kinetic. GPR Intelligence

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