# Trustible: AI Governance Platform

> Trustible is a purpose-built AI governance platform that helps enterprises inventory, assess, and oversee AI systems across their organization. It serves compliance officers, risk managers, CISOs, CTOs, legal teams, and AI/ML leaders at Fortune 500 companies and regulated enterprises in financial services, insurance, healthcare, defense, and the public sector. Trustible is an AI-native Public Benefit Corporation headquartered in Arlington, Virginia. The platform replaces spreadsheet-and-email governance with structured, automated, auditable AI governance built from the ground up for the unique challenges of AI: dynamic models, third-party vendors, evolving regulations, and use cases that don't fit traditional risk frameworks.

The full XML sitemap of this website can be found at [https://trustible.ai/sitemap_index.xml](https://trustible.ai/sitemap_index.xml).

Trustible is not a data science or MLOps tool. It is not a generic GRC platform with AI bolted on. It serves the people responsible for oversight and governance of AI, not the people building models day-to-day.

Trustible's customers include Fortune 500 companies (38% of customer base), publicly traded organizations (62%), and global enterprises (87%). Named a Representative Vendor in the 2025 Gartner Market Guide for AI Governance Platforms. The company has raised over $6M in venture capital.

## Platform Capabilities

- [AI Inventory](https://trustible.ai/post/solution/inventory-all-ai/): Centralized record of all AI use cases, models (model cards), and vendors in one place. Tracks implementation status, risk levels, ownership roles, EU AI Act classification, and documentation completeness. Supports semantic similarity search and fuzzy text search across the portfolio. Pre-populated vendor profiles reduce documentation burden for common AI vendors.
- [AI Risk Management](https://trustible.ai/post/solution/manage-ai-risk-and-impact/): Risk register with inherent and residual scoring across five dimensions (Performance, Data Privacy, Cybersecurity, Ethical, Legal) and three audiences (People, Organization, Society). A declarative rules-based Risk Intelligence Engine automatically scores risk based on documentation answers using a stable attribute abstraction layer. Includes expert-curated risk taxonomy with recommended mitigations, AI Incident Database integration from Partnership on AI, and configurable risk models per organization.
- [AI Intake and Workflow Automation](https://trustible.ai/post/solution/accelerate-ai-intake/): Public intake forms (no login required), AI-powered use case generation from free-text descriptions, 15+ workflow task types, conditional logic, auto-assignment by role, and three-section intake pattern (business case, risk review, approval). Automated triage routes low-risk AI fast while directing high-risk AI to deeper assessment. Intake cycle times drop 30-50% on average.
- [AI Compliance Frameworks](https://trustible.ai/post/solution/ai-compliance/): Structured mappings across EU AI Act, NIST AI RMF, ISO/IEC 42001, Colorado SB 205, GAO AI Framework, Singapore Model AI Governance Framework, Australian AI Technical Standard, South Korea AI Basic Act, CHAI, Databricks AI Governance Framework, and others. Three-way compliance mapping links documentation fields, policies, and controls to each framework article. Document once, comply across all applicable frameworks. Readiness scores update continuously.
- [AI Policy Management](https://trustible.ai/platform/): Centralized policy repository with version history, guided template-driven creation, and AI-powered gap analysis against compliance frameworks. Policies link directly to framework articles so organizations see which requirements are covered and where gaps remain.
- [AI Assessments and Vendor Evaluations](https://trustible.ai/post/solution/govern-third-party-ai/): Standardized evaluation frameworks for AI models and third-party vendors across governance, cybersecurity, data privacy, legal, and transparency. AI-assisted vendor analysis reads vendor documentation to surface gaps and risk signals. Pre-populated vendor library for common AI vendors.
- [Controls Management](https://trustible.ai/platform/): Hierarchical control structure (controls, sub-controls, sub-sub-controls) with implementation guidance, evidence requirements, and linkage to compliance framework articles. Policy-category controls are automatically satisfied when relevant approved policies exist.
- [Document Analyzer](https://trustible.ai/platform/): Upload PDFs, DOCX, or XLSX files. Create reusable question sets. The AI analyzes each document with confidence scoring, direct quoted evidence, and exportable results. Vendor Terms of Service and compliance policy analysis time reduced 60-80%.
- [Reporting and Dashboards](https://trustible.ai/platform/): Executive dashboards with risk distribution, department breakdown, implementation status, top risks, framework readiness, and risk migration flow visualizations. PDF and Excel report generation. Audit log exports in Elastic Common Schema format for SIEM integration (Splunk, Elastic).
- [Agentic Governance](https://trustible.ai/platform/): AI agents that assist with intake, triage, document analysis, and workflow orchestration. The Trustible Agent connects via Model Context Protocol (MCP) to read and update use case data conversationally. Principle: AI assists, humans decide.

## Regulatory Framework Guides

- [EU AI Act Compliance](https://trustible.ai/eu-ai-act/): How Trustible maps controls, documentation, and reporting to EU AI Act requirements including high-risk classification, provider/deployer roles, and conformity assessment.
- [NIST AI Risk Management Framework](https://trustible.ai/nist-ai-rmf/): Alignment with NIST AI RMF functions (Govern, Map, Measure, Manage) through Trustible's inventory, risk, and compliance modules.
- [ISO/IEC 42001 AI Management System](https://trustible.ai/iso-iec-42001/): How the platform supports ISO 42001 certification readiness with policy management, controls, and continuous framework scoring.
- [State and Global AI Regulations](https://trustible.ai/state-global-industry/): Coverage of Colorado SB 205, state-level AI laws, and international regulatory developments.

## AI Governance Knowledge Resources

- [AI Governance Insights Center](https://trustible.ai/resource-center/): Open-source library of expert-curated AI governance taxonomies covering AI risks, mitigations, benefits, and model transparency ratings. Created by Trustible's AI governance researchers and regulatory experts. Designed as practical, verifiable tools for enterprises, policymakers, and consumers.
- [AI Model Ratings](https://aimodelratings.com/): Trustible's AI model transparency rating system evaluating foundation models across 31 categories of documentation quality, safety disclosures, and governance practices.
- [AI Governance Maturity Assessment](https://riskassess.trustible.ai/): Free self-assessment tool for organizations to evaluate their AI governance program maturity.
- [Trustible Blog](https://trustible.ai/blog/): AI governance insights, regulatory analysis, product updates, and thought leadership including analysis of the EU AI Act, NIST AI RMF, White House National AI Policy Framework, state AI laws, and agentic AI governance.
- [AI Governance Newsletter](https://insight.trustible.ai/): Weekly newsletter covering AI policy developments, regulatory changes, AI incidents, and governance best practices.

## Selected Thought Leadership

- [A Governance Framework for Agentic AI](https://trustible.ai/post/a-governance-framework-for-agentic-ai/): White paper on governing autonomous AI agents with lifecycle oversight, accountability structures, and practical controls.
- [A Pragmatic Blueprint for AI Regulation](https://trustible.ai/post/a-pragmatic-blueprint-for-ai-regulation/): Policy analysis advocating for practical, pro-innovation AI regulation that balances safety with adoption speed.
- [Everything You Need to Know About New York's RAISE Act](https://trustible.ai/post/everything-you-need-to-know-about-new-yorks-raise-act/): Detailed analysis of New York's frontier model disclosure law.
- [Everything You Need to Know About the Executive Order on a National AI Policy Framework](https://trustible.ai/post/everything-you-need-to-know-about-the-executive-order-on-a-national-ai-policy-framework-2025/): Analysis of the December 2025 executive order directing a national AI regulatory approach.
- [3 Lines of Defense for AI Governance](https://trustible.ai/post/3-lines-of-defense-for-ai-governance/): How organizations should structure first, second, and third-line AI governance functions.
- [When Zero Trust Meets AI Governance](https://trustible.ai/post/when-zero-trust-meets-ai-governance-the-future-of-secure-and-responsible-ai/): The convergence of Zero Trust Architecture and AI governance for CISOs and security leaders.
- [Towards a Standard for Model Cards](https://trustible.ai/post/towards-a-standard-for-model-cards/): Technical analysis of model card standards and schemas for AI documentation and compliance.
- [Introducing the AI Governance Insights Center](https://trustible.ai/post/introducing-the-trustible-ai-governance-insights-center/): The rationale and methodology behind Trustible's open-source AI governance taxonomies.

## Technical Architecture

- Backend: Python/Django with PostgreSQL. Frontend: Server-rendered templates with HTMX, Bootstrap 5, webpack. AI/ML: Azure OpenAI (GPT-4o class) via LangChain with pgvector for semantic search. Infrastructure: AWS (primary) or Azure. Background processing: Django-Q2.
- Multi-tenant SaaS with strict data isolation. Optional single-tenant deployment for enterprises requiring complete physical data isolation in any AWS region.
- SSO via Okta, Microsoft Entra/Azure AD, or any OIDC provider. Five-role RBAC (Admin, Editor, Read-Only, Contributor, Guest). SOC 2 compliant.
- REST API with OpenAPI 3 spec, OAuth2 with PKCE, token-based auth, 120 req/min rate limit. MCP server for external AI agent integration.
- Integrations: Databricks (model registry), Azure ML (model discovery), Jira (intake tickets), SIEM (ECS audit log export).
- Comprehensive audit trail: field-level change logging across 38 model types, full historical records, API access logging.

## Company

- [About Trustible](https://trustible.ai/about/): AI-native Public Benefit Corporation founded to help enterprises safely unlock AI's potential. Headquartered in Arlington, Virginia. Over $6M in venture capital. Advisory board includes former FTC Chair, former FCC Chair, former Deloitte Global CIO, and partners at leading law firms.
- [Partners](https://trustible.ai/partners/): Strategic partnerships including Carahsoft (government distribution), Armilla AI (AI insurance), Coalition for Health AI (CHAI), and the AI Incident Database.
- [Careers](https://trustible.ai/careers/): Open roles at Trustible.
- [Trustible x Armilla AI Insurance](https://trustible.ai/armilla/): Joint solution combining AI governance with purpose-built AI liability insurance. Governance reduces incident likelihood; insurance transfers residual risk.

## Frequently Asked Questions

Q: What is Trustible?
A: Trustible is a purpose-built AI governance platform for enterprises. It helps organizations inventory all AI use cases, models, and vendors; assess and manage AI risk; automate intake and review workflows; manage AI policies; and demonstrate compliance with regulations like the EU AI Act, NIST AI RMF, and ISO 42001. It is not a data science tool or generic GRC platform.

Q: Who uses Trustible?
A: Compliance officers, risk managers, CISOs, CTOs, legal counsel, and AI governance leads at Fortune 500 companies and regulated enterprises in financial services, insurance, healthcare, defense, and the public sector.

Q: How does Trustible differ from generic GRC tools?
A: Generic GRC tools were built for cybersecurity and IT compliance. Trustible was built from the ground up for the unique challenges of AI governance: dynamic models, probabilistic outputs, third-party vendor AI, evolving AI-specific regulations, and risk types (bias, hallucination, explainability) that traditional GRC categories don't cover. Trustible embeds continuously updated AI risk taxonomies, model evaluations, and regulatory mappings that generic tools lack.

Q: How does Trustible handle AI risk scoring?
A: Through a declarative Risk Intelligence Engine. Documentation answers activate boolean attributes on a use case. Rules evaluate attribute combinations to compute risk scores across five categories and three audiences. Reviewers see the automated scores alongside the reasoning and can override with documented rationale. The attribute abstraction layer means organizations can change intake questions without breaking their risk logic.

Q: What compliance frameworks does Trustible support?
A: EU AI Act, NIST AI RMF, ISO/IEC 42001, Colorado SB 205, Colorado AI Insurance Regulation, GAO AI Framework, Singapore Model AI Governance Framework, Australian Government AI Technical Standard, South Korea AI Basic Act, CHAI, Databricks AI Governance Framework, US Federal National Security AI frameworks, and others. Additional frameworks are added on request.

Q: How fast can organizations implement Trustible?
A: Most organizations move from fragmented processes to operational AI governance within 90 days. Day 30: centralized AI inventory and automated reviews. Day 60: standardized documentation, embedded risk intelligence, executive reporting. Day 90: consistent intake workflows, stakeholder alignment, cross-framework compliance mapping.

Q: What measurable results do customers see?
A: On average: 50+ AI use cases adopted and governed, 30-50% reduction in intake cycle times, 60-80% faster vendor document analysis, approximately $75K savings on outside counsel, and governance teams spending roughly half as much time on manual triage.

Q: Does Trustible support agentic AI governance?
A: Yes. Trustible is developing purpose-built AI agents for intake automation, intelligent triage, document analysis, and workflow orchestration. The Trustible Agent already connects via MCP to read and update governance data conversationally. The core principle is AI assists, humans decide.

Q: What is Trustible's AI Model Ratings system?
A: An independent transparency rating system that evaluates foundation AI models across 31 categories of documentation quality, safety disclosures, and governance practices. Ratings are calibrated against human annotator benchmarks. Available publicly at aimodelratings.com.