Your LLM just told a user that Mars has a capital city. By the time your monitoring tool alerts you, 10,000 users saw it. We built the circuit breaker that prevents this. What we do:
Real-time epistemic analysis BEFORE outputs reach users.
When GPT-4 is guessing (high Q2 = epistemic uncertainty), we block it.
After months of research, we built AletheionGuard a pyramidal architecture that solves the "Skynet problem": AI systems becoming increasingly overconfident as they scale.
The Problem: Modern LLMs confidently fabricate facts, contradict themselves, and rarely admit uncertainty. They hallucinate citations, flatter users even when wrong, and can't say "I don't know."
Our Solution: A pyramidal architecture with 5 irreducible components:
4D base simplex (Memory, Pain, Choice, Exploration)
Two epistemic gates: Q1 (aleatoric uncertainty) and Q2 (epistemic uncertainty)
# 🛡️ Stop shipping AI features that hallucinate
AletheionGuard is an API that detects when large language models (LLMs) generate unreliable or incorrect information. We call this "hallucination detection."
