I. Encoding Laws & Policy
We translate laws, regulations, and internal policies into machine-checkable constraints — so agent behavior can be verified against the rules that govern a domain.
Verification Layer for AI Agents
Non-deterministic agents are doing deterministic, high-stakes work. Understanding agent drift becomes vital as regulated enterprises grant agents real autonomy, and as a growing share of production code is written and modified by agents faster than humans can review it. Align AI makes agent drift reproducible and verifiable, so it can be trusted and governed.
Talk to UsOur mission is to seek the truth
In most domains, verifying an agent is trivial — a game has a score, a compiler has a test. But the ground truth that governs the world's most complex work was never assembled in one place.
Some of it is codified — laws, regulations, and policies written for humans, not machines. Some of it lives in enterprise systems of record — knowledge bases, case histories, and operational data that encode how an organization actually decides. And some of it exists only in expert judgment — clinical reasoning, underwriting intuition, decisions that can't be looked up.
We call this the non-verifiable knowledge problem. Agents can't be trusted in these domains until their behavior can be checked against ground truth. Assembling that ground truth — encoding the rules, embedding the institutional knowledge, eliciting the expert signal — and turning it into a verification layer is the unsolved problem. Solving it requires new research, not better pipelines.
Our Research Pillars
Four classical orders of inquiry — each essential, each reinforcing the others.
II. Embedding Enterprise Knowledge
We ground verification in enterprise knowledge bases and systems of record — the case histories, precedents, and operational data that define how an organization decides.
III. Expert Signal Elicitation
We extract ground truth from what credentialed experts do, not just what they say — capturing the judgment that was never written down anywhere.
IV. Verification & Evaluation
We compose these sources into verification layers and evaluation frameworks — so agent drift can be detected, measured, and governed in production.
Our Team
Our team comes from Oscar Health, Apple, Microsoft, and Apella, with advisors from Harvard, Stanford, and Cornell.