AI Safety Infrastructure

Validate AI Decisions
Before They Execute

Multi-agent adversarial validation for high-stakes AI systems.
Wherever AI decisions carry real consequences.

01 — Mission

AI systems make critical decisions every second. Most fail silently.

Current AI validation approaches catch errors after damage is done. We intercept flawed reasoning before execution—using adversarial multi-agent systems that challenge every decision in real-time.

Pre-Execution Validation

Specialized critic agents analyze AI-generated rationales before any action is taken, catching failures that slip past traditional testing.

Domain Agnostic

Core validation architecture transfers across verticals—finance, healthcare, cybersecurity, autonomous systems—with configuration, not rebuilds.

Veteran-Founded

Built by combat veterans who understand that mission-critical systems require mission-critical validation. Failure is not an option.

02 — Technology

MiniCrit: Adversarial Validation at Scale

A patent-pending multi-agent framework where specialized critics challenge AI reasoning through structured adversarial analysis. The meta-agent synthesizes critiques into execution decisions.

System Architecture

INPUT
AI Signal
CRITICS
C1 · C2 · C3 · C4
META
M1 Synthesis
GATE
Execute / Block

03 — Results

Production-validated performance

0%
False Positive Reduction
0%
Model Accuracy
0+
Training Pairs Collected

Deployed 24/7 on live production systems. MiniCrit reduced false positive rates from 18% to 6%—validated through continuous operation and rigorous testing across diverse decision scenarios.

04 — Contact

Ready to validate your AI systems?

We're working with defense agencies, financial institutions, and autonomous system developers to deploy adversarial validation at scale.

Get in Touch