Audit-Grade Truth for Autonomous AI
At Acuityio, we are building the verification infrastructure that enables AI models and autonomous agents to be safely trusted with high-stakes decisions.
The Epistemic Challenge of LLMs
Large language models are probabilistic text predictors, not knowledge repositories. When an LLM hallucinates, it does so with the exact same linguistic certainty and fluent confidence as when it speaks the truth.
In our research benchmarks evaluating 1,000 real-world factual claims across 5 frontier models, models disagreed on 63% of claims while self-rating their confidence as 9/10 or 10/10 in over 76% of responses. Single-model self-checking is an illusion.
Our 3 Core Principles
Truth is reached through structured opposition. We pit frontier models against each other in debate before triangulating through independent auditor panels.
No model verdict is accepted without verbatim citations to authoritative primary sources: court decisions, statutes, medical databases, and peer-reviewed journals.
Every claim verification creates a permanent, immutable record containing all debate turns, reviewer fallacy tags, and full citation links.