AI governance from training to verification
Three products, MCG, TTU Router, and CoF Audit, built on the Conservation of Fidelity mathematical framework, covering training optimization, inference routing, and deterministic verification. Each works standalone. The stack multiplies value.
Five stages, one framework
How data flows through the stack
Attractor Mapping — Pre-deployment screening
Before any model reaches production, screen it against domain-specific scenarios to identify failure modes, including cases where the model produces dangerous output with high confidence.
MCG — Training optimization
Map the model's internal structure. Identify which layers are critical and which are redundant. Remove redundant layers without retraining. The model tells you what it doesn't need.
TTU Router — Inference routing
At runtime, measure quality on each response and route to the right-sized model. Easy queries handled cheaply. Complex queries get the full model. Provider-agnostic.
Safety Routing — Runtime safety layer
Detect safety-critical queries and flag cases where the model may be unreliable despite appearing confident. Route flagged queries through CoF Audit before delivery.
CoF Audit — Deterministic verification
The final gate. Safety contracts evaluate AI output deterministically. ALLOW or BLOCK, with a cryptographic audit trail. The responsibility gate between AI output and human action.
Not stitched-together tools
Every product is built on Conservation of Fidelity, one mathematical framework that connects model analysis, inference routing, and output verification. Insights from one product strengthen the others.
Existing tools: pick one stage
Some do monitoring. Some do output filtering. Some do model compression. Spanning training, inference, and verification with a shared mathematical framework remains an open gap.
Fidelity Horizon: all stages, one theory
Training insights inform runtime decisions. Model analysis generates verification rules. Each product strengthens the whole stack because they share the same mathematical foundation.
Interested in the full stack?
We walk through real, verified results. No slides, no mockups.