AI runs your AI compliance program — on the loop.
The Autopilot is your autonomous compliance officer. It scopes use cases, drafts policies, runs evaluations, collects evidence, and exports the audit bundle continuously. The work a manual compliance team does in quarters, the Autopilot does every day.
You don't hire a compliance team. You install one.
The old model: a manual compliance vendor charges $150K–$500K per year to do the same work every quarter. The new model: Autopilot runs it for you, continuously, with every approved trace.
- ×Quarterly engagement — your runtime moves daily
- ×Humans transcribe traces into spreadsheets
- ×Policy authoring takes weeks
- ×Evidence assembled at audit time, not continuously
- ×$150K–$500K/year + per-hour overages
- Runs on the loop — daily by default, on every approved annotation
- Reads traces directly — no transcription, no spreadsheets
- Drafts policies from observed runtime gaps in minutes
- Evidence bundle is continuously fresh, ready any day
- One platform fee; humans only approve material decisions
Seven steps, on autopilot, every day
The same loop a senior compliance officer runs by hand — Autopilot runs it for every AI system you ship, on the cadence you set.
Discover use cases
Autopilot reads runtime traces from Observe, clusters them into use cases (Customer Support Refunds, Legal Clause Summarizer, etc.), and proposes a risk tier per use case.
Pick frameworks
Based on industry, region, and use-case risk tier, it selects the applicable frameworks (EU AI Act Annex III, NIST AI RMF, ISO 42001, SOC 2, HIPAA) and shipped controls.
Draft policies
Where Guardrails has coverage gaps, Autopilot drafts policies in plain English with example traces — humans approve before they go live.
Run evaluations
It schedules taxonomy-driven Evaluation suites with the staged AI auditor, monitors pass rates, and flags regressions against a baseline.
Surface intelligence
Five intelligence jobs run per approved annotation: drift, taxonomy gaps, prompt sensitivity, factuality regression, policy coverage. Findings feed back into draft policies.
Loop in humans on judgment calls
Anything material — policy approval, risk acceptance, framework swap, bundle export — gets agent-action gated. Autopilot drafts; humans sign.
Export the audit bundle
Signed manifest with controls, traces, policy snapshots, eval results, audit log — one click. Continuously fresh, ready every day.
Watch the Autopilot work, replay any run
Every step streams over SSE. Every run is archived. Open last Tuesday's loop, see what it decided, what it deferred, and why.
Five intelligence jobs per approved annotation
Every time a human approves an annotation, Autopilot fires five jobs in the background — finding the patterns a human reviewer would miss across thousands of traces.
Drift detection
Compares current verdict distribution against rolling baseline. Flags when models silently degrade.
Taxonomy gap discovery
Finds outputs that don't fit any existing taxonomy dimension. Drafts new dimensions for review.
Prompt sensitivity
Reruns the same prompt with controlled perturbations. Flags low-stability verdicts.
Factuality regression
Cross-checks claims against the RAG knowledge base. Flags hallucination patterns by use case.
Policy coverage
Maps every output against Guardrails policies. Finds calls that ran without coverage.
Autopilot is the brain. The platform is the body.
You can use Observe, Guardrails, Evaluation, and Governance manually — Autopilot just runs them for you, on a continuous loop, with full transparency.
Compliance frameworks the Autopilot runs against
Autopilot FAQs
Frequently Asked Questions
Stop paying compliance consultants by the quarter. Run the program on autopilot.
Join the teams shipping safer AI with real-time evaluation, audit trails, and continuous improvement.