Platform
End-to-end AI compliance,
from prompt to examiner.
Meilynx is the compliance system of record for AI in financial services. One system enforces policy, governs agents, and produces examination-ready evidence — so the compliance budget buys one coherent audit trail, not a stitched-together stack.
- seq 1042Request sealedprompt · policy context
- seq 1043Decision sealedPII rule · redacted
- seq 1044Response sealedtokens · cost · outcome
→ Examination package
hash-linked · WORM archive · examiner-verifiable
One system, not four.
A mid-sized finance team shouldn't buy a model gateway, a DLP tool, an audit pipeline, and a model-inventory spreadsheet — then try to make them tell one story to an examiner.
Model gateway
routes, proves nothing
DLP tool
sees files, not prompts
Audit pipeline
logs, not evidence
Inventory spreadsheet
stale by exam day
The system of record
Meilynx
One system enforces policy, governs agents, and produces the examination-ready evidence — the layer that proves what your AI did, who governed it, and what backs the claim.
One position in the data path.
A single env-var change routes LLM traffic through the Meilynx proxy. From that one position it enforces policy pre-request and post-response, seals every decision into the audit chain, and attributes spend — while raw prompts and responses never leave your perimeter.
Inbound
Request
Outbound
Provider
Audit trail
Analytical store · WORM archive · Cryptographic hash chain
Every request, response, and policy decision captured to immutable storage in your environment. Examination-ready evidence — never delegated to the control plane.
Request
From your application
Policy
Model allow/deny · schema
PII / MNPI
Real-time detection
Cost
Per-request · budgets
Tools
Agent allow/deny
Provider
OpenAI · Anthropic · Azure · Google
Audit trail
Analytical store · WORM archive · Cryptographic hash chain
Capturing every call · 6-year floor (Fully Managed)
Shadow mode supported for safe rollout.
Deployed in a day, examined on your schedule.
Fully Managed deploys in about a day; self-hosted in one to two weeks. Either way, the path from first request to examination package is the same three steps.
Change one env var
Point your LLM base URL at the proxy. No SDK swap, no app rewrite — traffic flows through the data path the same day.
Publish policies
Start from framework presets, draft in shadow mode, then publish signed bundles your compliance team can read.
Export evidence
The audit chain accumulates from the first request. Export a curated examination package whenever an examiner asks.
Isolation is the architecture.
Not a configuration setting — the deployment topology itself.
- A per-customer isolated data plane in every deployment mode — your data never shares a boundary with another institution's.
- Raw prompts and responses never leave your perimeter; only hashed, aggregate metadata reaches the shared control plane.
- The data plane owns your audit trail — tamper-evident, WORM-archived, examiner-verifiable.
Deployment modes
See the trust boundary and per-mode matrix
Who operates what in Fully Managed and Self-Hosted — and the isolation invariant that holds in both.
What the platform does.
Each capability stands on its own and feeds the same examination-ready audit trail.
Controls that map to named regulations.
Not generic compliance — controls that map directly to the frameworks a financial-services examiner asks about.
Built for the data path.
Added latency
<1ms
Built-in regex, token, and schema checks at the data path
LLM providers
4live
OpenAI · Anthropic · Google · Azure OpenAI
Retention floor
6yr
Fully Managed production, per FINRA 24-09
Change to deploy
1env var
No SDK swap, no app rewrite
See it on your own traffic
A 15-minute walkthrough of inline enforcement, the audit chain, and the examination package.
Response within 1 business day