01

The problem with current autonomous sensing

Every LiDAR, camera, and radar system deployed in autonomous vehicles today produces a data format โ€” point clouds, image frames, radar returns โ€” that has discarded the causal structure of the physical observation. The AI that follows must statistically reconstruct what the sensor already knew. This is not a processing limitation. It is an architectural decision made before a single component was specified, and it cannot be fixed by better models or more compute.

02

How SCI IP addresses it โ€” from first principles

The ISS Platform (US 2026/0056318 A1) produces the participation matrix PM^kl as its native output โ€” not a derived product but the primary data format. The State Navigation system (US 20222245109 A1) receives PM^kl and navigates the causal state space of the scene. The sensor and the intelligence were designed together for this exact interface. The consequence: the autonomous system knows what caused each observation, not just what was statistically correlated with it.

03

Current status and next steps

The physical-ai.com seed round (M, 2026) is the bridge from IP-backed startup to prototype-validated Tier-1 partner. Tier-1 automotive suppliers are making sensing architecture decisions for the 2027-2029 production generation. The window for foundational technology decisions is open now and closes within 24 months.

IP position

US 2026/0056318 A1 (ISS Platform) and US 20222245109 A1 (State Navigation), both with July 2019 priority date. Both families cover autonomous vehicle sensing and intelligence as named primary applications.