Compliance-by-construction for AI.

Every AI call your team makes — every prompt, every multi-agent run, every Cursor session — passes a policy gate, lands in a tamper-evident audit log, and exports as a signed Evidence Pack your auditor can verify offline.

Built for CISOs and Risk Officers who need to defend AI use cases before a regulator does.

Proofpane Mission Control: 12 governance agents, live audit timeline with hash-chained events, Claude CLI embedded in the same view.
Mission Control · Claude CLI under one policy gate · click to try live
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What you get out of the box

Tamper-evident audit Cryptographic verification

Every AI decision lands in a cryptographically chained log scoped per tenant, so cross-tenant tampering is structurally detectable. Export as a signed Evidence Pack — a standalone offline verifier ships in the bundle so your auditor can verify it without backend access.

Audit timeline showing hash-chained events — every AI decision logged with cryptographic linkage between rows.

Compliance by construction NIST · ISO 42001 · EU AI Act

Control library aligned with NIST AI RMF, ISO/IEC 42001, and EU AI Act evidence expectations — pre-mapped per skill, with per-org overrides. A closed-set guard cross-checks every cited control ID against a curated truth set so fabricated references can't pass. Proofpane supports operational evidence; it does not replace legal, regulatory, or certification assessment.

Compliance dashboard: NIST AI RMF · ISO 42001 · EU AI Act · GDPR · SOC 2 framework coverage with per-control mapping to skills + per-org overrides.

Cost + Quality gates Multi-signal monitoring

Per-org monthly USD cap with audited refusal — over budget, the LLM call never fires. Multiple quality signals run on every output, with anomaly detection and triage workflow surfaced in the operator dashboard.

Quality dashboard: pass rate, hallucination rate, fabricated-ref count, by-skill / by-model / by-provider breakdowns + low-score triage queue.
/quality · pass rate · halluc rate · triage
Cost dashboard: monthly USD spend vs cap, 30-day sparkline, top spenders by skill, anomaly table.
/cost · spend vs cap · top spenders

Self-evolving with HITL Approval-gated

Two reflection loops, same approval contract. The first watches the audit log for drift, hallucination, and low-score signals, and proposes prompt edits against the org's own failure cases. The second tracks curated AI-research feeds and auto-sandboxes proposed updates against production behaviour. In both cases only the changes a human approves ever go live.

Internal reflection queue: proposed prompt edits awaiting human approval — every change goes through review before going live.
Internal reflection · audit-log driven
External reflection: research-feed scout that promotes high-relevance items into approval-gated sandbox sessions.
External reflection · research-driven

Visual workflows skills · multi-agent · scheduled

Compose governance tasks, multi-agent primitives (consensus and adversarial review), and scheduled triggers on a visual canvas. An AI builder edits the graph for you. Every node execution writes a row into the same audit chain — the canvas is the planning view, the chain is the proof.

Multi-agent workflow canvas — Classify AI System → Impact Assessment 3-way consensus → Map Obligations, with live execution status and skill palette.
Works wherever your team uses AI
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Built in Aotearoa New Zealand · Louie.Lu@proofpane.com
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