Verifiable AI Systems

Prove what systems claim.

We build and operate production AI infrastructure with verifiably traceable system behavior. Continuous control probing ensures every assertion binds to a source record.

Rigour follows consequence

Component criticality classification

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Identify failure modes

Classify by consequence

Apply engineering rigour

System components are analyzed to identify potential failure modes and their impact on operational integrity.

Each identified failure mode is classified by its consequence, separating low-risk speed from high-consequence assurance.

Rigour in review, testing, and deployment is then concentrated on high-consequence failure modes, optimizing assurance efforts.

Residuals are stated

Explicit bounds detailing what deployed models cannot verify.

We publish explicit operational bounds detailing what our deployed models cannot verify. This transparency ensures clarity on system capabilities and limitations.

Claims bind to sources

Automated verification pipelines

Source record decomposition

Generated outputs are decomposed into atomic claims. Each claim is then traced to its originating source record for verification.

Evidence binding

Atomic claims are bound to specific source records via unique, stable identifiers. This ensures verifiable traceability for every assertion.

Automated release gating

Verified claims are automatically gated before release. This pipeline ensures only source-bound assertions enter production systems.

Engagement parameters and initial phase pricing.

Understand how work starts, what a first phase costs, and what you own at the end. Direct route to engagement.