For compliance teams pursuing an AI strategy
Audit-native controls
Compliance controls that record evidence as they run, with full context. Every decision is captured, attributable and immutable. The chain of custody is ready when the auditor asks.
problem
The audit-vs-automation gap
For regulated firms, automation and audit defensibility are at odds. Tools can save time but reconstruct the audit trail after the fact. Manual review is defensible but doesn't scale. Firms with needs beyond standard frameworks have nowhere to turn.
01
Manual evidence assembly
Preparing for an audit takes an enormous amount of manual work. Traces are pulled from disparate systems, connected back to control objectives by hand and compiled into evidence packets.
02
Off-the-shelf tools don't fit your controls
Generic compliance tools cover standard frameworks but can't serve firm-specific needs well, and the evidence they produce still gets assembled after the fact.
03
AI strategies add a new governance burden
Your own AI workflows generate consequential decisions that now need to be controlled and evidenced, on top of every existing control.
How it's different
Audit-native compliance controls
From manual evidence assembly to audit-by-query.
Evidence as a byproduct
Each control operation produces a finding, backed by an evidence record written as it runs: control version, policy clause, input, decision, actor, model version, timestamp, rationale. That record is attributable and immutable, built into the type of object the system produces. No reconstruction.
Custom controls without custom audit plumbing
Author firm-specific controls from your proprietary context: internal guidelines, scorecards or jurisdiction-specific overrides. Get the audit trail for free. Bespoke rules and audit defensibility stop being a tradeoff.
Composes with your AI
Your AI agents and workflows plug in directly. Read decision traces to ground your AI's work, or run AI actions through controls to make them audit-native too. No model lock-in.
Architecture
How a control is built and run
You build your own controls and keep them current as the rules change, with every change reviewed and versioned. When a control runs, it runs in the write path, so the full context of each decision is captured the moment it happens, never reconstructed from logs after the fact. The record is immutable and append-only, and when the auditor asks, the answer is a query.
See it in action
What you get
Everything your control program needs
Custom-control authoring
Compose firm-specific controls from your proprietary context, without forcing them into a standard framework.
Scored findings and guidance
Every control operation produces a finding scored for risk, with remediation guidance the team can act on.
Atomic, queryable evidence
Every firing writes a tamper-evident, attributed record to an immutable store. Pull audit-ready packets on demand, with scoped access for auditors and regulators.
MCP read for your AI
Your AI workflows query the decision trace through a stable, versioned, permissioned interface. No model lock-in.
MCP write for AI governance
AI actions flow through controls before they commit, so they become controlled, evidenced activities with the same trace schema as every other control.
Governed change workflow
Policy updates, regulation changes and control revisions flow through propose → review → approve → version. No silent drift.