The compliance system of record for AI in finance, insurance, healthcare, and HR.

Regulated organizations now run generative AI somewhere: a copilot, an agent, a customer-facing feature. Very few of them can answer the examiner's questions about it cleanly. Which models are in use, how they are supervised, what stops sensitive data from leaking, and where the records are.

Other material processes carry controls, named owners and an evidence trail. Examination findings now ask the same of AI.

An examiner asks for two things: the control that acted on a request, and the record that shows it ran. Meilynx produces both: policy enforced inline in the request path, and examination-ready evidence end to end.

That is what we mean by the compliance system of record: the one system that owns the audit layer an examiner cares about and can prove what your AI did.

Meilynx sits inline in the AI request path. From that one position it enforces policy before the request and after the response, seals every decision into a tamper-evident audit chain, and attributes cost and risk, while raw prompts and responses never leave your perimeter. Each deployment mode keeps your data in infrastructure dedicated to your organization.

Every request passes through that position. The control cannot be sidestepped, and the record comes from the component that made the decision.

The bar for correctness is high. Every control decision is recorded, and the record has to hold up under review years later. The latency budget is measured in milliseconds, and every change is held to it.

We write architecture decisions down before we build them, and every change passes review and automated gates before it reaches production.

• Inline by design

  Every control sits where the request has to pass. Enforcement and evidence come from the same component, at the same moment.

• Verifiable evidence

  The audit chain is tamper-evident, and an examiner can verify its integrity independently of us.

• Isolation as the invariant

  Dedicated infrastructure for every customer and environment. Raw prompts and responses never leave your perimeter.

• Measured before claimed

  Latency and throughput figures come from load campaigns we run and repeat. A number we publish is one we can reproduce.

Meilynx is co-founded and built by engineers who have spent their careers on infrastructure that is not allowed to fail: at Google, Microsoft, and BlackRock. That background spans keeping global cloud infrastructure reliable and efficient at scale, leading platform and AI-enabled product engineering, and building analytics inside financial services.

Governing AI in a regulated organization is an infrastructure problem and a compliance problem at once: the enforcement sits in the data path, the latency budget is real, the audit trail has to hold up years later, and the people who sign off on it answer to a regulator. The team has built on both sides.

Meilynx is headquartered in Bellevue, Washington, and builds for compliance, risk, and security leaders in financial services, insurance, healthcare, and HR. Our security and compliance posture, and how to reach our security team, are documented in the Trust Center.

We work closely with the teams who deploy us, from the first architecture conversation through examination. We are hiring across engineering and customer programs.

If governing AI well is on your desk, we would like to hear from you at hello@meilynx.com.