meilynx
AI compliance platform · Finance · Insurance · HR

Prove your AI is compliant.Continuously.

From prompt to examiner, one audit chain. Meilynx sits in front of every model, agent, and tool your teams use. It enforces policy inline, seals each decision into a tamper-evident record, and turns that record into the evidence an examiner asks for.

AI traffic interception · proxyready
prompt "
Custom policies
organizational rules · allow/deny
PII / MNPI
detect · redact at request layer
Agent / MCP interception
tool calls inspected · drift · approvals
Budget
cost caps per project · team · customer
LLM provider
Anthropic · OpenAI · Azure
downstream
tamper-evident audit chain
every request sealed & hash-linked — even blocked ones
allowed
9f3a1c
blocked
7e02b4
gated
c41d92
Examination package
sealing…

Controls mapped to the frameworks your examiners cite

All frameworks

Presets ship in the product. HIPAA Technical Safeguards and NIST AI RMF are enforceable through the policy engine today, scoped with your compliance team.

What Meilynx governs

Models, agents, and the traffic you cannot see.

AI leaves your building on three paths. Meilynx sits on all of them and writes every decision to one record.

01 · Model traffic

Prompts and responses

Calls to OpenAI, Anthropic, Google, and Azure OpenAI pass through the proxy, where policy runs on the content of each request and reply.

  • PII and MNPI detection, redaction, or block
  • Model allow-lists and budget caps per team
  • Prompt-injection and jailbreak screening
Inline enforcement

02 · Agents and tools

Tool calls and MCP actions

Tool calls are inspected at the boundary they cross. Drift from an approved baseline is flagged and high-risk actions wait for a second approver.

  • Tool allow and deny lists per agent
  • Drift detection on prompts and tool grants
  • Two-party approval for consequential actions
Agent governance

03 · Shadow AI

Traffic that bypasses the governed path

Connect a provider's admin account and Meilynx compares what the provider billed with what came through the proxy. The gap is your bypass rate, per provider.

  • Bypass rate scoped to the access you grant
  • Method disclosed on every number
  • Sealed into the same audit chain
Coverage measurement
What it does

Comply. Govern. Optimize.

Enforcement, evidence, and cost control from one proxy in your own infrastructure. The screens below come from a demo project; a 15-minute walkthrough shows them on your own traffic.

01 / Comply

Evidence an examiner will accept.

Each request, response, policy decision, and human review lands in write-once storage in your environment, and each control maps to a named regulation.

  • Hash-chained audit trail an examiner can verify independently
  • Examination packages for NYDFS 500, FINRA 24-09, NAIC AI, and SOC 2
  • 6-year WORM retention floor (Fully Managed, FINRA 24-09)
  • Reviewer sign-off and remediation tracking
Compliance / Overview
Compliance overview showing per-framework coverage scores for the EU AI Act, FINRA 24-09, ISO/IEC 42001, and NYDFS 500

02 / Govern

Policy enforcement at the request layer.

Prompts and responses are inspected in flight and blocked, redacted, or logged by policy, per team, per app, and per model.

  • Model allow / deny lists and token limits per workflow
  • Built-in rules for PII and MNPI detection, model access, cost, agent safety, and schema, extensible with WASM and webhook validators
  • Prompt injection and jailbreak screening
  • Cost caps in real time, with draft, review, and shadow mode before publish
Govern / Findings
Findings page with counts by severity, category, and action, and a table of recent redacted, blocked, and warned requests

03 / Optimize

Cost tied to outcomes and risk.

LLM spend alongside the business outcomes and compliance events it produced, by team, app, and model.

  • Cost analytics tied to business outcomes
  • Per-team budgets with hard caps, attributed before month-end
  • AI health monitoring with anomaly detection
  • Custom KPIs by workflow, team, and customer segment
Economics / Cost and outcomes
Spend versus successful outcomes chart by model over a month
Architecture

Two planes. One trust boundary.

Your data plane runs in infrastructure dedicated to you, managed by us or operated by you, and it owns the audit trail. The shared control plane distributes signed policy bundles and receives hashed metadata, never raw payload.

Your environment

Managed or self-hosted · isolated either way

Trust boundary
  • Application

    Your apps & agents

  • Meilynx Proxy

    Validators · streaming · audit emission

  • Audit Trail

    WORM archive · hash chain · examination export

Raw prompts & responses never leave this boundary.

Per-customer isolated data plane in every deployment mode

Telemetry

metadata

Bundles

policy-as-code

Meilynx control plane

Managed SaaS

  • Policy authoring

    Signed bundles · policy-as-code

  • Compliance console

    Posture · waivers · examination packages

  • Telemetry rollup

    Metadata only · token counts · rule outcomes

No raw payload data ever reaches the control plane.

Deployment modes

Same isolation. Different operator.

Fully Managed or Self-Hosted. The difference is who runs the infrastructure.

Dimension

Fully Managed

Meilynx operates per-customer infrastructure · ~1 day

Self-Hosted

Customer operates everything · 1 to 2 weeks

WORM immutability

Retention-locked object storage

Live

Customer-managed object storage

Customer
Retention floor

6 yr prod · 30 d staging · 1 d test (FINRA 24-09)

Live

Customer-set (proxy default: 90 d)

Customer
Encryption at rest

AES-256-GCM + per-customer CMEK

Live

Customer-managed

Customer
Integrity Pack

Included

Live

Customer-operated

Customer
Verification surface

Hash chain · examiner-verifiable

Live

Hash chain · customer-operated

Customer
Proxy operated by

Meilynx

Live

Customer

Customer

By the numbers

Added latency, p95

<0ms

Measured under load with the full detection stack running

Requests in the load test

0.0M

August 2026 campaign, zero failures

Retention floor

0yr

Write-once archive in Fully Managed production, per FINRA 24-09

Change to deploy

0env var

No SDK swap and no rewrite. About a day managed, one to two weeks self-hosted

Why Meilynx

Examiner-grade, not log-grade.

Logging what your AI did is table stakes. Meilynx proves it, with a record an examiner can verify on their own and evidence that comes from live traffic rather than last quarter's document.

CapabilityMeilynxDLP / CASBSIEM / log exportBuild it yourself
Enforces policy inline, before the call leaves your perimeterYesPartialPartial
Reads prompt and response content, including PII and MNPIYesPartialPartial
Write-once, tamper-evident record rather than a log exportYes
Curated examination packages per frameworkYes
Integrity an outside auditor can re-verify on their ownYes
Detects agent drift and gates high-risk actions behind a second approverYesPartial

A category comparison, not a product-by-product rebuttal. Most tools can log what your AI did. The rows below the first two are where examination evidence gets produced, or does not.

You can check the record yourself. An examiner or your own auditor can recompute the hash chain with an open verifier at any time. The proof does not depend on trusting Meilynx.

Independent verification
Coverage by region

What applies where.

US federal and state rules, the EU framework, and the international standards auditors fall back on. Controls map to named regulations, not to compliance in the abstract.

Trust & compliance posture

SOC 2 Type I· Report issued
GDPR
Source access· Design partners · under NDA
Data residency· Per-customer isolated

Review our full security posture in the Trust Center

From the blog

Latest thinking.

Notes on AI governance: examination posture, policy enforcement, and what regulators are asking.

View all posts →
Ready to evaluate Meilynx?

See it on your own traffic.

A 15-minute walkthrough of inline enforcement, the audit chain, and the examination package, on live data.

No commitment. Response within one business day.

Regulatory updates

When a regulator changes what an AI examination asks for, hear about it first.

Short notes on SR 26-2, NYDFS 500, FINRA, the NAIC bulletin, the EU AI Act, and the employment-AI statutes, plus what we ship. A few emails a month.