Your AI agents are making decisions faster than your organization can learn from them. Lyrastone is the governance layer that closes that gap — not with more dashboards, but with a system that corrects itself.
Patent pending · US #64/019,650 · BCN – NYC
McKinsey’s latest benchmark puts average AI governance maturity at 2.3 out of 5. Your agents repeat the same mistakes. Your teams lose trust in the tools. Your compliance posture is a spreadsheet someone updates quarterly. BCG calls the human cost “AI brain fry”: 39% more errors, 34% planning to quit, productivity dropping after a third tool is added. The gap between what AI can do and what organizations can govern widens every quarter.
Lyrastone sits beneath your agent stack — a behavioral governance layer that watches how AI decisions land, learns from every correction, and tightens its own standards automatically. Every failure generates a fix, a rule, and an enforcement mechanism. The system earns autonomy the way your best people do: by proving it can be trusted, one decision at a time. Not a dashboard. Not a chatbot. Infrastructure.
Built on a single reusable engine: signal aggregation, scoring, and alerting at enterprise scale. Each product adapts the same infrastructure to a new GRC domain.
Third-party risk scores in one API call. Five government data sources — NVD, CISA KEV, EPSS (exploitation prediction), CVE severity, and GitHub Security Advisories — aggregated into a composite vendor risk score. Third-party risk management automation for teams that cannot afford to guess about their supply chain.
View on RapidAPIRegulatory change intelligence, delivered before it matters. Monitors federal registers, agency guidance, and enforcement actions across jurisdictions. Surfaces what changed, what it affects, and how long you have. For compliance teams who would rather prepare than react.
Early AccessVVP is product one. The same infrastructure generates eight GRC intelligence products: contract risk, audit readiness, insider threat signals, policy drift detection, and more. Each adapts the core engine in two to three weeks. The portfolio compounds. The architecture is already built.
Join the waitlistFour months. Every day. What follows is not a roadmap. It is the system, running.
Each hook was triggered by a real failure, not a policy document. Patent filed US #64/019,650 — six mathematical functions for trust calibration.
Grounded in peer-reviewed frameworks. Published openly. We do not move faster than the science.
Double-loop learning (Argyris) applied to agentic AI systems. How behavioral governance transforms error correction from event into infrastructure.
Coming soonBayesian inference meets loss aversion (Kahneman & Tversky). How the Lyrastone trust score predicts future behavior with r=0.39, p<0.0001.
Coming soonBCG research synthesis. Why 39% more errors and 34% attrition risk are governance failures, not technology failures — and what the fix looks like.
Coming soonLyrastone was founded by Chris Byrd after 15 years leading enterprise transformation across Fortune 500 financial services, global consulting, and technology companies. Chris delivered MIT’s digital transformation research to enterprise clients and led governance programs spanning regulated industries and complex organizational change.
The pattern was always the same: governance was the answer to digital transformation. Then AI changed the question. It is no longer “how do we manage the technology.” It is “does the person trust the technology enough to let it help?”
Chris built Lyrastone because his own brain needed it. What started as a personal survival tool became a patent-pending system with measurable results and applications across every industry deploying AI.
“The pattern was always governance. Then AI changed the question — from managing the technology to earning the trust of the people using it.”Chris Byrd — Founder, Lyrastone