Building the deterministic runtime and infrastructure stack for the physical AI economy. Where enterprises need verification and deployability, not just bigger models.
Enterprises don't need bigger models. They need determinism, verification, and deployability.
OEMs and federal programs are stuck with probabilistic systems that produce heatmaps instead of diagnoses. Without causal ground truth, there's no path to certification, no systematic improvement, and no way to deploy at scale with confidence. The infrastructure gap is holding back the entire physical AI economy.
Three integrated layers delivering deterministic, verifiable, and certifiable AI systems—from edge to cloud.
The first verifiable diagnosis system for model failures. OEMs and federal programs finally get root causes, not heatmaps. Inspector provides deterministic failure analysis with full traceability—enabling certification-grade debugging and systematic improvement.
Self-correcting perception wrapper that transforms any vision model into a deterministic, verifiable system. Delivers 4–10× reliability uplift in 12–18 months through continuous self-validation and adaptive correction—without retraining.
Synchronizes entire autonomous fleets into a systemically consistent, certifiable platform. Enables cross-vehicle learning, unified policy enforcement, and real-time performance validation—the infrastructure layer for scaled physical AI deployment.
Not bigger models. Not more parameters. Determinism. Verification. Deployability.
Acuion's architecture maps directly to the AI infrastructure thesis Race Capital leads—building the foundational layer that enables physical AI to move from research to production deployment.