The Architecture of Provable Trust
Three proprietary systems working in concert to transform AI decisions from opaque outputs into transparent, verifiable, and legally defensible judgments.
Deterministic Causal Tracing
Every AI decision creates a complete chain of custody. Know exactly which inputs drove which outputs—not statistically, but deterministically. This isn't feature importance or attention weights. It's a mathematical proof of causation.
Traces exact causal path for every single decision
Provides statistical feature importance scores
Complete Visibility
See the exact path from input data to final decision. No black boxes, no approximations.
Audit-Ready Documentation
Generate regulator-ready documentation automatically. Every decision comes with its own proof.
Real-Time Analysis
Causal analysis completes in under 12 milliseconds. Production-grade speed for enterprise scale.
Structural Logic Mapping
We analyze the geometric structure of reasoning itself—finding hidden contradictions and logical gaps that statistical approaches miss entirely. This is mathematical verification of decision logic, not pattern matching.
Proves logical consistency with mathematical certainty
Checks for keyword-based policy violations
Structural Verification
Goes beyond surface analysis to examine the fundamental structure of decision logic.
Contradiction Detection
Identifies when your AI's reasoning contradicts itself—even across thousands of decisions.
Policy Alignment Proof
Mathematically verify that decisions align with your stated policies and regulatory requirements.
Adversarial Self-Correction
Every judgment passes through an internal tribunal that actively tries to break it. When flaws are found, the system corrects itself in real-time—before errors ever reach production. This isn't monitoring. It's continuous adversarial validation.
Adversarial verification with automatic real-time correction
Post-hoc bias detection reports delivered monthly
Multi-Agent Verification
Independent verification agents stress-test every decision from multiple adversarial angles.
Automatic Correction
When flaws are detected, the system diagnoses, corrects, and re-validates automatically.
Certified Output
Decisions are graded: Certified (high confidence) or Provisional (with documented caveats).
Three Layers. One Verdict.
Every decision passes through all three systems in sequence. The result is a judgment that's been traced, verified, and stress-tested.
Not Just Different. Fundamentally Better.
See how the Glass Box approach compares to legacy solutions.
| Capability | AEQUITAS | Legacy Solutions |
|---|---|---|
| Explainability | Deterministic causal chains with mathematical proof | Statistical approximations and feature importance |
| Consistency Verification | Mathematical proof of logic integrity | Rule-based keyword matching |
| Error Handling | Self-correcting with complete audit trail | Manual review and intervention required |
| Audit Readiness | Automatic, real-time documentation | Post-hoc report generation |
| Latency | Under 12 milliseconds | Minutes to hours |
Ready to open the box?
See how AEQUITAS can transform your AI governance from a liability into a competitive advantage.