New, with Accorian: a real-time AI governance framework for control drift in enterprise AI.Read the framework
AI Governance · AIUC-1
AIUC-1
The agent-level certification standard for AI, mapped to the evidence your build already produces. Six control categories, proven continuously from the same trace pipeline behind the build.
StandardAIUC-1
ScopeAgent-level
Categories6
Six control categories, one evals pipeline.
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
What it isType: Agent-level certificationIssuer: AIUC Inc.Categories: Data, security, safety, reliability, accountability, societal riskStatus: Certified by AIUC or an authorized third party
At a glance
An agent-level standard, six control families wide.
Control category → Evidence
The standard names the categories. We produce the evidence each one needs.
AIUC-1 control categoryEvidence we produce
DataPersonal-data handling, minimization, retention, cross-border, subject rightsPer-tenant handling log, classification + source pointer, cross-border inventory, subject-request workflow
SecurityAccess, authentication, prompt-injection defense, tool-call authorizationAuthorization exception log, prompt-injection detection rates, per-invocation auth trail
SafetyHarmful-output filtering, jailbreak resistance, human oversightVersioned safety baseline, violation incident log with resolution trace, human-in-the-loop audit
ReliabilityGroundedness, factuality, multi-turn consistency, fallbackRolling 30-day groundedness SLO, per-agent consistency metric, tested fallback behavior
AccountabilityDecision provenance, audit logs, human ownership, change historyDecision chain per interaction, human-owner registry, change log for policy, baseline, prompt, model
Societal riskBias and fairness, demographic parity, impact assessment, disclosurePer-use-case bias evaluation, versioned impact assessment with owner, populated disclosure templates
One pipeline, every framework
How the AIUC-1 evidence gets produced.
Trace
production behavior
Classify
sensitivitysource
Evaluate
per-use-case baseline
Map
every framework
Pack
on demand
What auditors look for
Three evidence patterns that pass.
01
Versioned baseline per use case
A signed-off threshold. The underwriting and marketing agents differ, with timestamps and owners.
02
Trace lineage to a human owner
Every decision points to the data, policy, baseline, and person behind it.
03
Freshness attestation
Every artifact timestamped. Ask what the system did yesterday at 3:47pm and get an answer.
AIUC-1, asked plainly
Direct answers.
No. AIUC Inc. or an authorized third party certifies. We produce the evidence the certifier needs, kept current.
Keep the evidence map connected
Pairs cleanly with the rest.
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.