Dave is charged with defining and executing on strategy for ModelOp Center, paving the way for customers to overcome their governance challenges and unlock the value of AI.
Artificial intelligence has always promised automation for enterprises. But today, a new autonomous frontier is opening. Welcome to the age of Agentic AI: autonomous systems that pursue goals, make decisions, and take action across your enterprise systems without step-by-step human instruction.
This is the beginning of the agentic era—one where software agents, powered by LLMs, SLMs, and planning systems, collaborate like human teams. But while the architecture is new and powerful, so are the risks: data exposure, unpredictable actions, runaway costs, and non-compliance with internal and external policies. Given that these systems go beyond answering questions and can take initiative, you need to be absolutely certain they’re acting within bounds.
That’s why ModelOp has launched a comprehensive toolset for governing Agentic AI at scale—including a new Agentic AI Chat Interface, live inventory of agent-based systems, controls for protecting from mis-aligned usage, and real-time cost tracking to provide transparency into cost/benefits of AI use cases.
These new tools deliver two breakthrough capabilities:
- Agentic AI Chat Interface – A conversational layer that allows CIOs/CAIOs, AI and governance leaders, AI owners, and other stakeholders to query, analyze, and summarize key AI governance insights about AI systems in ModelOp using natural language. Furthermore, the agentic tools can even register new AI risks or trigger AI lifecycle actions.
- Governance for Agentic AI – Given the rapid rise of Agentic AI, our customers need to ensure that it's being used safely, securely, and in a financially sustainable manner. To do this, ModelOp is introducing three new services–the agent service, metrics service, and the proxy service–to address the growing demand for governing Agentic solutions. These services provide the ability to quickly import A2A agents and MCP tools, per-use-case approvals for agentic systems, network-level blocking of unapproved agents, inline protections (e.g. prompt injection attacks), and detailed token and cost tracking—ensuring enterprises maintain visibility, control, and assurance as AI systems act autonomously.
Governance Must Evolve
With Agentic AI
When agents are making decisions–using models, taking actions, and changing logic—all without waiting for human approval, you need a control tower. Furthermore, when autonomous systems are running 24/7, governance is about more than ethics and compliance—it’s about ROI.
Without governance, Agentic AI creates a new breed of enterprise risks:
- Security risks
- Incorrectly updating, or worst case, deleting systems and data
- Accessing or updating enterprise data to which they should not have access
- Inadvertently sending internal data outside of the customer firewall
- Bringing in an agent that has vulnerabilities or other security risks
- Policy violations
- Agents taking action that is not an approved corporate procedure
- Unintended regulatory violations
- Inability to explain agent actions to audit
- Uncontrolled costs
- Overactive agents calling expensive LLMs or vendors deploying consumption pricing models
- Citizen AI developers deploying 1000’s of agents without an understanding of the cost implications
ModelOp enables enterprises to address these challenges through our technology-agnostic, governance platform that works for all model types - from ML and GenAI to agents and Agentic AI.
The ModelOp Agentic AI Solution
We built ModelOp’s Agentic AI solution on three core principles—Visibility, Control, and Assurance—because enterprise leaders need more than innovation—they need accountability, cost discipline, and trust at scale.
1. Visibility
Agentic AI introduces complexity, fast. ModelOp delivers live visibility into every agent running across your enterprise—what models they call, which tools they access, and what business outcomes they drive. You get a unified view of agent-based use cases, enabling cost attribution, accountability, and alignment with enterprise priorities.
New capabilities include:
- Agentic AI Chat Interface – A conversational layer that allows CIOs, CAIOs, AI and governance leaders to query, analyze, and summarize key AI governance insights about AI systems in ModelOp using natural language. Furthermore, the agentic tools can even register new AI risks or trigger AI lifecycle actions.
- Agentic Inventory–tracking and visibility of all components–tools, agents, llm’s–that compose an Agentic solution. Given agents can make decisions, they need to be registered and verified–just like a human would register for a Driver’s License. The ModelOp agentic inventory provides detailed forward-and-backward traceability of agentic systems: (a) identifying all use cases that leverage a given agent, model, or agent tool (b) all agents, models, agent tools, etc. that compose a use case. This bi-directional traceability allows for quickly identifying all business use cases that may be affected by a new vulnerability or other issue identified for a given agent or model.
- Import A2A and MCP–quickly import your agents and agent tools into ModelOp Center. This service queries remote MCP and A2A servers, imports agent card information and tool definitions, captures related assets, and kickstarts governance automations—so your agent inventory is always up to date and audit-ready.
2. Control
With business teams demanding rapid adoption of Agentic solutions, ModelOp helps you stay in control by enforcing policies to safely and responsibly use agents.
New capabilities include:
- Block unapproved agent traffic: network-level blocking of all unapproved agents through the new ModelOp proxy service, ensuring that no MCP or A2A traffic can traverse unless the agent agent tool is registered and approved in the ModelOp inventory.
- Lifecycle automation: ensures Agentic systems follow the company’s AI governance policies, including calculating the risk rating, mapping the relevant risks and controls, and obtaining the appropriate approvals.
- Usage & cost tracking: transparency into the token usage and associated costs for each AI use case, allowing business leaders to be fiscally responsible and make informed decisions into which AI solutions are driving the most value. This capability lets leaders answer questions like:
- Which agents are costing the most?
- Where and when are we overspending on foundation model tokens or AI API calls?
- What are the costs for a given agentic business use case?
3. Assurance
Innovation without governance is a risk multiplier. ModelOp provides the assurance you need with full audit trails.
New capabilities include:
- Metrics tracking: track metrics (execution, usage, etc) directly from the ModelOp proxy, from external feeds, or directly with key AI providers (e.g. OpenAI).
- Inline controls: real-time guardrails on agents/agent tools to protect from mis-aligned actions (prompt injection attacks, PII leakage, etc.). ModelOp will detect any violations and block the request or response immediately, ensuring that all agentic traffic is safe, secure, and ethical.
The Future of AI Governance Is Agentic
If you’re only tracking prompts and outputs, you’re missing the full picture. The future of enterprise AI requires governance for:
- Agents that act autonomously
- Systems that evolve dynamically
- Interactions that span tools, APIs, business units, and even external customers and partners
That’s what we’ve built at ModelOp. Not a bolt-on GRC dashboard, but a platform designed from the ground up to govern the most advanced AI architectures emerging today.
ModelOp is the control tower for ALL your AI initiatives.
Ready to See It in Action?
If you’re experimenting with agents or planning to deploy Agentic AI in the next 12 months, now’s the time to take control.
👉 Request a demo to see how ModelOp can become your AI Control Tower—governing everything from ML to multi-agent systems with the speed, scale, and trust your enterprise demands.
