Physics-Grounded Simulation for AI Validation & Synthetic Data
TRL 4 Ready
Sovereign EU Tech
The Data Gap
The Problem: AI Hallucinations
Training AI for LWIR/MWIR sensors with real data is prohibitively expensive. Standard models fail to understand complex thermodynamics and atmospheric attenuation.
Our Solution: FNT RTSim SW
A physics-based Digital Twin that simulates real-time heat exchange, emissivity, and thermal inertia, generating pixel-perfect synthetic datasets for AI grounding.
Core Competencies:
Physics-Based Rendering (PBR)
High-fidelity Sensor & Noise Modeling
100% Automated DRI AI Labeling
Sim-to-Real Pipeline
From Virtual Thermodynamics to AI QKV Tokens
1. PBR Engine
THERMODYNAMICS
2. Sensor Model
LWIR ATTENUATION
3. AI Grounding
CLASS: TARGET_UAV
DRI TOKENS
root@fnt-rtsim:~#
Data Gen
10k+ FPS
DRI Labeling
100% Auto
Sim-to-Real
> 98% Acc
EU Funding Targets
Horizon CL4
DIGITAL-EMERGING-09
Advanced Local Digital Twins using AI for Early Warning.