Your AI systems are making decisions.
Can you prove they're governed?

Companies deploying AI face accelerating regulatory pressure — EU AI Act, NIST AI RMF, ISO 42001, and a wave of state-level AI laws. Most governance is still checkbox compliance that does not survive contact with production agents.

HUMMBL builds the infrastructure that makes governance operationally real. Not policy PDFs. Runtime systems with append-only audit trails, signed delegation, kill switches, and circuit breakers — wired into the agents and adapters that actually touch your data.

What we do

Assess

Governance maturity scoring against NIST AI RMF and ISO 42001. Map gaps between written policy and runtime reality. Five interactive readiness assessments — free, instant, no email gate.

Implement

Runtime governance modules: append-only audit trails, HMAC-signed delegation tokens, 4-mode kill switches, per-adapter circuit breakers. Stdlib-only Python — zero third-party runtime deps.

Verify

Adapter conformance testing for third-party AI tools entering your stack. Verify vendor AI systems meet your governance requirements before they reach production data.

Why most governance frameworks fail

Mandating governance into organizations where people don't trust the system produces compliance theater — checkboxes filled, behaviors unchanged. HUMMBL is built on the inverse premise: trust infrastructure first, governance second. Transparency, receipts, and structural conditions for adoption — so the controls actually land. Governance that ships, not governance that's imposed.

Proof points (verified, today)

15,600+

Automated Tests

Runtime Dependencies

Live Adapters

120

Reasoning Models

Framework Coverage

NIST AI RMF ISO 42001 EU AI Act NIST CSF 2.0 SOC 2 Colorado SB 24-205 Singapore IMDA

Governance Modules — what runs in production

Coordination Bus

Append-only TSV log for polycentric agent coordination. 70,000+ messages processed with zero data loss; every agent action receipted.

Kill Switch (4 modes)

DISENGAGED → HALT_NONCRITICAL → HALT_ALL → EMERGENCY. Sub-2-second mean halt time. Operator-controlled, audit-logged.

Circuit Breakers

Per-adapter CLOSED / HALF_OPEN / OPEN states. Failure-isolation for every external service the agent talks to.

Delegation Tokens

HMAC-SHA256 signed authority transfer between agents. Append-only governance bus records every delegation.

Adapter Receipts

Every adapter call returns a receipt — agent, target, payload hash, status, latency. Governance proof per call.

Agent Identity Registry

Trust-tiered identity per agent (owner / trusted / probationary). Scope restrictions enforced at write paths.

Readiness Assessments

Five interactive assessments: EU AI Act, Colorado AI Act, ISO 42001, Singapore Agentic AI, NIST AI RMF.

Base120 Reasoning

120 mental-model operators across 6 families (Perspective, Inversion, Composition, Decomposition, Recursion, Systems).

Production case studies

Production Agent Governance at Scale

Governing 12+ concurrent AI agents (Claude, Codex, Gemini) across trust tiers via shared message bus. 70,000+ messages, zero unauthorized-action review, 7 internal policy violations caught and contained. Read →

Cross-Framework Compliance Mapping

Single governance codebase satisfying ISO 42001, EU AI Act, and NIST AI RMF simultaneously. Arbiter quality score: A (99.5/100). Estimated 70-90% cost reduction vs. separate compliance programs. More →

Agentic AI Readiness Assessment Platform

Five interactive assessments built and shipped — first interactive tool for the Singapore Agentic AI Framework. Zero signup friction, instant SVG radar reports, drives consulting via demonstrated expertise. Try →

Engagement model

Three entry points: (1) Free assessment — radar score, gap map, framework crosswalk in 15 minutes; (2) Implementation engagement — wire kill switch, circuit breakers, audit trail into your existing AI stack; (3) Verification — review evidence for a third-party AI tool before it touches production data. Solo-founder pricing; outcomes referenceable on hummbl.io/case-studies.

Your AI systems are making decisions.Can you prove they're governed?