ModelOp makes enterprise AI governance software for CIOs, CTOs and AI governance leaders in large, regulated organisations. It gives them one record of every AI asset they run, from traditional machine learning models to generative AI, agents and AI embedded in vendor SaaS applications.
The problem it solves is AI that spreads faster than anyone can approve, monitor or evidence it for regulators.
At A Glance
| Vendor | ModelOp |
|---|---|
| Category | AI governance and AI lifecycle management |
| Deployment | On-premises, private cloud or hybrid |
| Agentic AI | Agent discovery, MCP and A2A import, agent cards, runtime policy at the AI gateway |
| Customers | Prudential Financial, Manulife |
| Market classification | AI Governance & Compliance |
What ModelOp Does
Large enterprises run many kinds of models built by different teams on different tools, and few can say what is in production, who approved it and what it costs. ModelOp sits above existing MLOps and development tools rather than replacing them. Governance is built into the automated delivery workflow instead of added as a separate checkpoint, so a use case is registered, reviewed and monitored as part of getting it into production. Policies can be modelled for the EU AI Act, NIST AI RMF, OCC SR 11-7 and ISO 42001 alongside internal enterprise policy.
Products
Enterprise AI Command Center
The Command Center is the system of record for AI, aimed at organisations that need to know what AI they run and prove it is under control.
- An inventory covering ML, GenAI, agents and vendor AI
- Continuous discovery of unregistered AI, such as custom GPTs
- Automatic capture of code, prompts, agent cards, configurations, dependencies and data usage
- Standard use-case intake, risk classification and tiering
- Approval workflows across Security, Privacy, Data, IT, Architecture, Legal, Risk and Compliance
- Monitoring for bias, drift, performance, data stability and prompt vulnerabilities
- AI FinOps tracking token usage, cost, throughput and tool invocations in real time
- Portfolio dashboards by business unit, geography, lifecycle stage and risk tier
AI Delivery Engine (MADE)
MADE is the framework underneath the Command Center. Customers and systems integrators plug their own agents into it, so the agents carry out work across the AI lifecycle themselves, guided by policy.
How It Works
The Command Center installs on-premises, in a private cloud or in a hybrid set-up, and is not a public SaaS service. It references data where it already lives rather than copying it. It connects to more than 50 technologies, including MLOps tools, model registries, major LLM providers, GRC and ITSM systems, and AI and API gateways such as Kong.
| Component | What it does |
|---|---|
| System of record | The inventory, with metadata, documentation and risk tier for each use case. |
| Workflow and approvals | Intake and reviews move through one traceable workflow across the governance functions. |
| Runtime enforcement | An AI gateway sits in the path of live AI traffic, and policy from the Command Center is enforced there. |
| Evidence and audit | Model cards, validation summaries and evidence are captured across the lifecycle for audit. |
Agentic AI Capabilities
Agents are governed through the same inventory and workflow as models, with three additions specific to them:
| Tool discovery | MCP-connected tools are discovered automatically |
|---|---|
| Agent import | Agents are imported through MCP and A2A together with their tool inventories, so each one arrives in the record with what it can call |
| Runtime protections | Inline protections at the AI gateway block prompt injection, PII leakage, unsafe tool use and misaligned agent actions |
Company Background
| Founded | 2018, by a team that had put models into production for large global banks and financial institutions. |
|---|---|
| Headquarters | Chicago, United States. |
| Leadership | Dave Trier, CEO; Jim Olsen, CTO; Pete Foley, co-founder and former CEO. |
| Recognition | Included in the 2026 Gartner Magic Quadrant for AI Governance Platforms. |
Note: This overview is compiled from ModelOp’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.