Adversarial AI Infrastructure

The signal is in
the divergence. divergence.

Divergence IP builds:

Multi-model adversarial panels that surface hallucinations and drift no single model can see in itself
Document analysis that maps divergence at the claim level
Pre-action verification that intercepts AI agent decisions before execution
Human affirmation gates that enforce a cryptographic confirmation trail before any autonomous action is released

What we do

Multi-Model Convergence

Independent models run adversarially against the same input. Divergence is preserved as a first-class output — never flattened to a single verdict.

Pre-Action Verification

Machine-readable artifacts are verified before downstream consumption. A cryptographic attestation chain ties every verdict to its evidence.

IP Portfolio

Five provisional patents filed covering adversarial convergence architecture, inline pre-action verification, and human affirmation gating for autonomous AI systems.

Flagship Product

The Arbiter — TA

The divergence map is the output.

Every competitor runs a single AI against a database. The Arbiter runs an independent adversarial panel against the same document and outputs the divergence — surfacing the drift and hallucinations a single model cannot see in itself. The divergence map is the output. Nothing else does this today.

Adversarial Panel

Multiple independent model families with distinct roles run blind to each other against every document.

Per-Claim Divergence

Output is graded per claim — verified, contested, or unverifiable — not a binary block or allow.

Cryptographic Attestation

Every verdict is signed. The chain from input artifact to panel decision is tamper-evident.

Patent Applications

Built for high-stakes document analysis where a single model's hallucination is not an acceptable failure mode.

The signal is in the divergence. divergence.