Runtime governance infrastructure
Agentic governance workflows
with AI policy at dispatch
Witness AI governs autonomous and semi-autonomous agent workflows — enforce AI policy on every irreversible step, not just at session start. Runtime BLOCK rules, human approve gates, and cryptographically signed receipts prove what ran.
Agent roster — policy gates
- research-agentpolicyALLOW
- outbound-agenthuman gateESCALATE
- tool-call-agentai-policyBLOCK
- publish-agentapproveALLOW
Institutional alignment
Why runtime AI policy is now board-level
Independent research on agentic AI adoption and governance gaps — cited on our Sources page. Product metrics labeled separately.
Session-start prompts and static acceptable-use docs cannot govern tool calls at dispatch. Buyers expect request-level AI policy enforcement on every irreversible agent step — not after the fact.
[10] NIST (2024). Generative AI Profile — operational controls for generative and agentic systems. Primary source ↗Enterprises must define agent autonomy levels, decision boundaries, behavior monitoring, and audit mechanisms — with policies formalized for development, deployment, and usage.
[2] McKinsey & Company (2025). Seizing the agentic AI advantage. Primary source ↗Governance must answer: Can we reconstruct agent decisions end-to-end? Do we have rollback when something goes wrong? — proof of control, not policy slides.
[3] McKinsey (2025). Trust in the age of agents. Primary source ↗Framework alignment maps
Alignment maps only · not certification
Built for teams governing agent workflows
Educational framework mapping only — not legal advice, certification, or regulatory approval. Full crosswalk on Sources.
Agent fleets run fast. AI policy still lives in slide decks.
Ungoverned agent actions
Agents call tools, send messages, and publish output without a durable policy check at the moment of action — only after something goes wrong.
Policy at session start only
Acceptable-use docs and system prompts are not runtime governance. McKinsey calls for decision boundaries and audit mechanisms at scale — enforced at dispatch on every irreversible step.
McKinsey agentic AI governance · ref [2]No proof of enforcement
Chat logs are not an audit trail. Witness AI records ALLOW, BLOCK, and ESCALATE with signed receipts you can replay.
WitnessBC portfolio
WBC-FLOW — publish with sourcing, corrections, and proof
High-stakes civic and institutional updates need documented sourcing, visible corrections, and tamper-evident receipts — not automated pay-to-publish.
WBC-FLOW project
NGO, newsroom, or civic team — tip → approve → publish loop with Proof Lab evidence.
WBC-OPS retainer
Ongoing governance ops — corrections discipline, receipt archive, escalation playbooks.
Proof Lab + film
Interactive BLOCK · ESCALATE · tamper-FAIL scenarios — STYLE-B1 hero film when Screen Studio ships.
Open Proof Lab →WitnessBC only — Proof Lab · Civic toolkits · receipts on disk
Explore
Runtime governance — page by page
Drill into platform architecture, live proof, pricing, and cited sources.
Get started · 6 chapters
Guided onboarding — Proof Lab, workflows, tamper-FAIL, book live proof.
PlatformObserve · Govern · Prove
Dispatch architecture, autonomy tiers, and capability grid.
LoopGovernance loop
Six gates from intake to proof — each with machine receipt codes.
ProofLive receipt replay
BLOCK · ESCALATE · ALLOW · tamper-FAIL · interactive terminal.
CompareDispatch vs prompts
Runtime AI policy vs session prompts and checklists.
PolicyAI policy + diligence
Versioned packs · procurement checklist · export posture.
PricingFlow + Ops
Free packs · first install · retainer.
FAQQuestions answered
Agentic governance, Flow install, and policy scope.
SourcesReferences & crosswalk
Checked primary sources and framework mapping.