Devoudit is the observability layer for AI governance. Treat policy like production infrastructure — with SLOs, beacons, and an audit trail that can't be drafted in a Google Doc.
Tool approval checklist, data classification, incident playbook, vendor DDQ, employee 1-pager. Zero to documented, one afternoon.
Most AI policies are PDFs nobody reads. The ones that work are rules with tooling attached — a signal that fires when the rule is followed, and an incident when it isn't.
"Employees must not share proprietary data with external AI services."
"Beacon BCN-014 fires when PII is sent to any endpoint outside the approved-vendor list. SLO: 99.9%. Breach → incident."
Write the rule as code. Bind it to a data class, an endpoint, and an SLO target.
beacon "pii.egress" slo 99.9 owner @sec
Drop an agent at the egress. It watches without blocking. Small, boring, fast.
devoudit agent --watch egress --ruleset pii
Every event produces a signed, timestamped signal. That signal is your audit trail.
bcn.fire(ok) at 2026-04-24T09:12 sig 0x8f…ea
Violation → on-call alert, incident, postmortem. Same muscle you already have.
alert routed pager · SEC-rotation status: triage
If your compliance program can't answer "was this rule active last Tuesday at 3pm?" — it's documentation, not policy.
Your SRE team already knows how to make abstract quality goals measurable and alertable. We've been doing it for uptime for fifteen years.
The bet behind Devoudit: the same muscle works for AI governance. Below, ten concepts your engineers already live by — and their 1:1 translation.
Your platform team already runs this playbook. We just wire it into your policy surface.
If it can't be expressed as an SLO, it's an aspiration — not a policy.
Beacon events are signed, immutable, and queryable. Your auditor gets a URL, not a screenshot.
Design partners shape the beacon library. Two slots left in the current cohort.