ModelOp, the Enterprise AI Command Center for Fortune 500 and Global 2000 enterprises, today announced its newest release, ModelOp Center 3.5. With deeper out-of-the-box integrations across Microsoft and Amazon, it centralizes AI agent governance for enterprises running AI on more than one development, execution and agent platform. New and enhanced integrations with Microsoft Agent 365, including agents built in Copilot Studio and Foundry, as well as Amazon Bedrock AgentCore and Amazon Quick, bring AI agents into ModelOp’s centralized system of record, where they are managed through automated lifecycle workflows and linked to their respective business use cases.

Enterprise AI no longer lives in one place. A business team builds an agent in Copilot Studio, a development team runs another on Bedrock AgentCore, and AI teams vet and offer approved LLMs across several providers. Most enterprises know which AI platforms they’ve bought. Far fewer can say which agents and models run on them, which use case each one supports, who owns it, whether the right controls were applied and what it costs to run an agentic use case.

“Enterprises are deploying AI across Microsoft, Amazon, OpenAI, and private infrastructure, yet no single platform provides CIOs, business owners, and AI governance leaders with comprehensive visibility and control,” said Dave Trier, CEO of ModelOp. “You can’t govern what you can’t see, and identifying an agent is only the first step. Business leaders need to understand its purpose, who is accountable for its actions, and whether it operates within established corporate policies. ModelOp Center 3.5 delivers that oversight through its centralized Enterprise AI Command Center, integrating Microsoft and Amazon agents with automated governance that reduces operational risk, strengthens accountability, and accelerates enterprise AI adoption.”

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Integrations That Go Beyond Discovery and the Inventory

ModelOp Center 3.5 connects to the platforms that enterprises use to build and run AI, including business-user agents in Microsoft Agent 365, Copilot Studio, and Amazon Quick, developer-built agents in Microsoft Foundry and Amazon Bedrock AgentCore, frontier models from Amazon Bedrock, OpenAI, and MCP tools hosted across multiple servers.

ModelOp’s AI discovery service, now connected to each of these platforms, compares what it finds against the enterprise’s approved inventory to surface unregistered and shadow AI. The integrations then carry each asset through the rest of its lifecycle:

• Automated lifecycle management. A newly found agent starts a workflow that enforces the enterprise’s policies and standards. For example, ModelOp imports it into the system of record, applies an initial risk tier, maps risk-proportional controls and routes approval to the right governance and control partners.
• Business use case context. Each agent and model are tied to the business use case it serves, along with its owner, controls and lifecycle stage, so leaders can manage AI as a portfolio of business investments.
• Usage tracking. Token usage is tracked by use case and model, showing leaders what each use case consumes across providers.

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Built for the Heterogeneous AI Enterprise

Microsoft Agent 365 and Amazon Bedrock AgentCore give enterprises strong technical control over the agents running on each platform, but individually lack the enterprise-level delivery and control required to align with corporate processes and policies.

ModelOp provides that control with a single system of record for ML, GenAI, agentic AI and vendor AI wherever it was built. Low-code, no-code and pro-code AI are managed in ModelOp’s Enterprise AI Command Center, so teams keep freedom of choice while enabling operational control of their vendor agents, models, and tools.

That starting point sets ModelOp apart from IT service management platforms extending toward AI and from execution platforms anchored to one vendor’s agents. ModelOp was built around the AI lifecycle and the business use case, and it works alongside the ITSM, GRC, security and data systems enterprises already rely on. ModelOp was ranked highest for the AI Agent Governance Use Case in the 2026 Gartner® Critical Capabilities for AI Governance Platforms report.

“Enterprises shouldn’t have to choose between giving teams the freedom to build on their preferred platforms and giving the CIO control,” Trier said. “Enterprises are adding more agent platforms everyday, and as a result, visibility is fragmenting and management can’t keep up. ModelOp sits above all of them, so the enterprise has one place to understand, govern and deliver the AI its teams build.”

AI FinOps in ModelOp Center 3.5

ModelOp Center 3.5 moves AI cost accountability from the token to the business use case with comprehensive AI usage tracking and reporting. Because each agent and model ModelOp finds is already tied to a use case and owner in the system of record, tracked token usage is attributed to that use case automatically. Leaders can see which use cases and models drive the most usage, compare models and providers side by side, and get alerts on material changes in consumption.

Discover how ModelOp Center 3.5 is transforming enterprise AI governance, accelerating agent deployment, and bringing greater visibility and control to AI operations. Read the launch blog to learn more.