New, with Accorian: a real-time AI governance framework for control drift in enterprise AI.Read the framework
AI Governance
AI Governance
Govern the AI you can see, and the AI you can't. Discover shadow AI and shadow MCP, prove policy in the workflow, and produce framework-mapped evidence on demand.
Scope2 wk
Evidencesource
Owners4
The quick audit is the fast read under AI Governance.
Every claim in the report traces back to source evidence, ownership, and the workflow decision it supports.
Valuefund next
Riskcontain now
Fluencytrain where work changed
At a glanceContinuous, not point-in-timeFramework-agnosticShadow AI + Shadow MCP discoverySR 11-7 · ISO 42001 · NIST AI RMF · EU AI ActEvidence mapped to named owners
What a first governance assessment surfaces
Illustrative shape of the assessment, not a single customer.
How it holds
One pipeline. Two outputs.
Production traces flow into one measurement engine. The operating view and the audit pack are the same evidence in two formats. There is no second pipeline.
Production traces
drifthallucination ratepolicy violations
Measurement engine
continuous evalowner mappingcontrol evidence
Operating View
liveread daily by the operator
Audit Pack
on demandSR 11-7ISO 42001NIST AI RMFEU AI Act
Built by us
We build the products behind this.
01
Wayne, the AI adoption engine
Discovers every AI tool in use, governs it with policy-as-code mapped to NIST AI RMF, ISO 42001, and AIUC-1, and proves the value. getwayne.app
Open02
asymmetric, agent integration testing
High-fidelity, disposable clones of the SaaS tools an agent acts in, so integrations are tested and scored before they reach production. getasym.dev
OpenDiscovery
Find what is running before anyone signs off.
01
Shadow AI discovery
Unapproved tools, embedded SaaS AI, and personal accounts on consequential workflows. Each finding gets a risk read and a named owner.
02
Shadow MCP discovery
Unauthorized MCP servers and tool calls wiring agents to your systems of record. The new attack surface as agents become composable.
03
Policy evidence in the workflow
Policy that lives where the work happens. Every material output ties to a reviewer decision, a control, and a trace.
Four lenses, one pipeline
What the four auditors actually ask.
SR 11-7
Model risk
Development, validation, and ongoing monitoring. The spine US examiners already apply.
ISO 42001
Certification track
What procurement asks for. Continuous evidence underneath, audit pack on demand.
NIST AI RMF
Govern, map, measure, manage
Artefacts for each function, sourced from one trace pipeline.
EU AI Act
Post-market duty
Risk classification, data governance, monitoring, incident reporting. Same traces, no second pipeline.
Two depths of assessment
Quick audit vs continuous governance.
The quick audit is the fast assessment. Governance is the continuous one.
Quick AuditAI Governance
ShapeOne independent assessmentAlways-on evidence stream
CadenceFast, point in timeLive, continuously refreshed
OutputBoard-ready opinionOperating view + audit pack on demand
Engagement
Two ways teams engage on the risk side.
01
Evidence pipeline
Always-on. Production traces in, framework-mapped evidence out. Operating view and audit pack from one source. The default after a maturity read puts governance on the roadmap.
02
Remediation Advisory
A bounded, incident-driven engagement. Triggered by drift, a regulator question, vendor exposure, or a certification ask. We stand up the evidence stream around the incident and hand back an operating loop.
Common questions
Direct answers.
No. It is the fast entry read under governance. Governance is the continuous version of the same evidence.
Specialist AI builder, across the board
One builder, across the board.
We take your AI from strategy to outcome, with governance, audit, and evals built into every build. Start with a discovery call, or a quick audit.