Trustible is an AI governance platform for enterprises that need to know where AI is being used, what risks it carries and whether it meets regulation. It gives governance, risk and legal teams one place to take in new AI use cases, assess them, watch them in production and produce audit evidence.
The problem it solves is visibility: AI use cases spread faster than reviews can keep up, and regulation such as the EU AI Act expects evidence that each one was assessed. Trustible maps its controls to more than 20 frameworks and sits alongside existing GRC tools rather than replacing them.
At A Glance
| Vendor | Trustible |
|---|---|
| Category | AI Governance & Compliance |
| Deployment | SaaS platform |
| Agentic AI | Built-in AI assistant and agentic workflows for governance tasks |
| Customers | Leidos, Guardian Life, Molson Coors, Olympus, Korn Ferry |
| Certifications | AICPA SOC 2 |
| Funding | A reported $6M or more in venture capital |
| Market classification | AI Governance & Compliance |
What Trustible Does
Most enterprises have more AI in production than their governance teams know about. Trustible closes that gap by treating governance as one lifecycle, from the moment a use case is proposed to the evidence an auditor asks for, so that evidence builds up as a byproduct of each decision instead of being assembled before an audit. Teams can run intake and risk programmes without any MLOps integration. Risk taxonomies and framework mappings are kept up to date by Trustible’s AI governance experts, using lessons from real-world incidents, and people stay in control of every decision.
Products
Intake
Intake replaces email chains and spreadsheets with structured workflows for proposing and approving AI use cases. It holds the inventory of models, agents, vendors and compliance documentation, and tracks each use case through Proposed, Pilot, Live, Rejected and Other. Sections, tasks, assignees, personas and approval stages are configurable, and assessment templates come pre-built by use case type, vendor or risk level. Low-risk items go to a light approval and higher-risk ones to full review, with every decision and decision-maker logged automatically.
Manage Risk
Manage Risk scores every use case the same way across Performance, Data Privacy, Cybersecurity, Ethical and Legal categories, so reviews reconcile. Pre-built risk cards span more than 40 risk dimensions, and a Risk Registry suggests risks and mitigations such as hallucination, data exposure or prompt injection. It calculates inherent and residual risk and starts an impact assessment as soon as risk crosses a set threshold. Reviewers can override a score with a documented rationale, backed by a field-level audit trail.
Monitor
Monitor ties internal signals (cost, quality, drift, safety) and external signals (vendor changes, incidents, regulation, litigation) to each use case. Nine pre-built metric categories are mapped to NIST AI RMF, ISO 42001 and the EU AI Act. Threshold alerts trigger re-assessment, review dates can be recurring or event-driven, and the Monitoring Hub shows alerts, reviews and inventory in dashboards.
Comply
Comply lets teams document each control once and link it to the matching requirement in every framework it covers. Evidence packages bundle the records auditors ask for, gap analysis marks requirements as covered, partial or missing, and executive dashboards show readiness by framework.
How It Works
Trustible runs as a hosted web application. Most customers have intake and first risk assessments running within a reported 30 days, with intake, governance, monitoring and compliance fully deployed by around day 90.
| Component | What it does |
|---|---|
| Unified AI inventory | The shared record of use cases, models, agents and vendors that every module reads from and writes to. |
| Governance workflows | Intake answers feed an automated risk score, which routes each use case to the right review depth and reviewer with context filled in. |
| Monitoring signals | Metrics come from vendor APIs, first-party telemetry and subject matter expert review, and alerts open re-assessment workflows. |
| Evidence layer | Intake decisions, risk assessments and approvals are timestamped against the use case record, exported per framework and passed to existing GRC systems. |
Agentic AI Capabilities
AI Assistant
A built-in assistant drafts new use case proposals, searches the AI inventory, pulls details on specific use cases and searches the risk and mitigation taxonomy. In Monitor it answers plain-language questions such as what changed on a use case and when. In the Risk Hub, Answer with AI explains its answers and flags items for the reviewer to verify, and in the Compliance Hub it answers coverage and gap questions.
Agent Governance
AI agents are first-class entries in the inventory alongside use cases, models and vendors, and the platform includes agentic AI observability for internal AI systems.
Company Background
| Headquarters | Washington DC area. |
|---|---|
| Legal form | AI-native Public Benefit Corporation. |
| Leadership | Gerald Kierce, CEO and Co-Founder; Andrew Gamino-Cheong, CTO and Co-Founder. |
| Investors | Lookout Ventures, Harlem Capital, Tau Ventures, Inner Loop Capital, Alumni Ventures, FoundersX, VamosVentures and JHH VC. |
| Recognition | Included in the inaugural 2026 Gartner Magic Quadrant for AI Governance Platforms. |
Note: This overview is compiled from Trustible’s publicly available information as of 3 November 2026. It is provided for information only. NHI Mgmt Group does not endorse any vendor, and nothing on this page represents the opinions of NHI Mgmt Group.