Agent Management
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How it Works
Lead responsible agentic transformation with full agentic workflow lifecycle management, all in one platform.
Connect MCP-tools securely
Power agents to execute across processes using your trusted business information.
Contextualize
AI-ready data
Fine-tune agent accuracy with proprietary business context, curated business definitions, and a single source of truth.
Control agentic workflows
Innovate at the speed of trust with universal governance across agents, tools, and APIs.
Full Agentic Workflow Lifecycle Management
Centrally manage the agentic workflows from Boomi and third-party providers with robust security, in-depth observability, and multi-region deployment options.
Agent Management Capabilities
Centralized Governance
One registry across 30+ providers with full observability, usage and token analytics, anomaly detection, and audit trails
Enterprise-Grade Security
Protect every human, agent, and data interaction with 15+ security and compliance certifications including ISO 42001
Flexible Runtimes
Deploy on-premises, hybrid, or cloud, and in local regions for compliance and sovereignty
Agent Lifecycle Management
Design, test, and deploy agents with built-in guardrails using no-code and templates
Agent Context
Ground agents with proprietary business knowledge, semantic meaning, and a single source of truth
MCP-enabled Tools
Turn enterprise assets into secure and governed MCP servers for agents with comprehensive API management
Agent Marketplace
Discover proven, pre-built agents and solutions from our trusted network of leading AI partners
Agent Integration
Integrate multiple agents, APIs, integrations, data, directly into business processes
Agentic Workflow Library
300+ templates to skip generic starting points and tailor to specific department and industry needs
Supercharge enterprise AI innovation with ready-to-deploy AI Agents
Discover ready-to-deploy AI agents, customizable agentic workflows, reliable AI connectors, and foundation and fine-tunable models to supercharge enterprise AI innovation.
Govern Your Agentic Future
Why Boomi for Agent Management
Universal Governance
Register agents across providers with built-in observability, always audit-ready.
Flexible Deployment
Host in the cloud, on-premises, or with a completely managed, zero-footprint solution.
Built for Today and Tomorrow
The only constant in AI is change. Scale agentic workflows that aren’t tied to a single ecosystem. No vendor lock-in.
Two Categories, One Leader
A Leader in both 2025 Gartner® Magic Quadrant™ for API Management & 2025 Gartner® Magic Quadrant™ for Integration Platform as a Service
Power of the platform
Leverage the power of the Boomi Enterprise Platform.
Manage agent lifecycle
Design, govern, and orchestrate all AI agents at scale.
What our customers are saying
Agent management resources
Explore all resources
Frequently asked questions
AI agents are software programs that can autonomously reason, make decisions, and take actions to achieve specific goals. As digital workers, they are designed to perform tasks for or with humans. These tasks can range from supply chain inventory adjustment to sales optimization across any given industry. According to The Australian, approximately 52% of firms view AI agents as pivotal for future growth, with 42% recognizing the potential of multi-agent systems.
AI agent management refers to the strategic oversight and optimization of AI agents throughout their lifecycle, from development and deployment to governance and maintenance, ensuring secure and seamless integration into business and technical workflows. It aligns AI initiatives with business goals while promoting ethical and responsible AI use.
As AI adoption grows across industries, so does agent sprawl, a proliferation of unmanaged AI agents from different providers operating within a business. As employees independently adopt AI tools, many businesses may already be using shadow AI, bypassing established IT security protocols without even realizing it. Managing these AI agents effectively is crucial to preventing sprawl and maintaining robust control. Key aspects of AI agent management include lifecycle management, governance, and observability. These proactive measures enhance AI reliability, mitigating security risks and building trust in AI agents.
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