Dify Recognized in Gartner®’s First Magic Quadrant™ for AI Agent Management Platforms. What It Means to Us.

Gartner has published its first Magic Quadrant for AI Agent Management Platforms and Dify is recognized as a Niche Player. It is a meaningful moment for our team as an AI Agent Management Platform. You can read more in our press release.

We also see a larger shift behind this recognition. Enterprises have learned to build individual agents, and now they need to know which agents are running, who can change them, and whether they are doing their jobs well. As more teams put agents to work, managing them becomes a challenge of its own.

From the First Agent, to the Hundredth

When the first agent works, other teams soon want one too. Before long, agents are running across different departments, often with different owners, tools, and models. By the time an enterprise is building its hundredth agent, a new question emerges.

How does it manage them all once they are in production?

That's the question we have been working on at Dify.

What Exactly is Agent Management

Agent management is not a separate task that starts after an agent is built. At Dify, we see it as one continuous process with three closely connected parts:

• Build. Create, test, publish, reuse, and improve agents as needs change.
• Govern. Know who owns each agent, who can use or change it, what data it can access, where it runs, and which models it uses.
• Operate. See what happens after launch, find problems, and track usage, performance, and cost over time.

Picture an HR team that builds an internal agent to answer questions from its policy library. When it works, Finance wants one for expense rules and IT wants one for troubleshooting guides. Each team should be able to build around its own knowledge, while the company controls who can access each source and who can change each agent. It also needs to see which agents employees use, where answers fall short, and what the growing program costs. Building an agent is just a beginning, while enterprises need all three once agents enter production.

From Building to Managing Agents at Scale

We started with a simple idea: teams should be able to unleash the power of AI without building the platform underneath. As enterprises put more agents to work, we support them through deployment and ongoing operations. We give enterprises control over where agents run, freedom to choose their models, and visibility into what happens after launch.

• The deployment choice is yours. Dify Enterprise can run in your VPC, on premises, or in an offline environment, so you can keep agents within your security and data boundaries.
• Model choice stays in your hands. Use commercial or locally deployed models and select what fits each task, your data requirements, and your budget.
• See how agents perform and what they cost yourself. Use logs and monitoring to observe individual runs, token usage, latency, and cost.

Your existing identity and security systems still remain part of the picture. Dify Enterprise supports single sign-on, automated user provisioning, permissions down to individual workflows, and audit logs that can be sent to your SIEM. At a leading global bank, Dify Enterprise supports six business units across five environments (Dev, SIT, UAT, Test, Production) with releases following governance standards aligned to the bank's core systems.

We also make growth easier to budget for. Dify Enterprise is offered through a fixed annual platform fee, with no per-agent charge or markup on model tokens.

We see the scale of adoption at Maersk, which replaced its in-house AI platform with Dify Enterprise. By late 2025, Maersk had deployed around 90 AI applications across customer experience and other business areas, serving 25,000 active users. Its use cases span customer support, email handling, and invoice audits, bringing AI into everyday operations across the business.

Learn more about how leading companies are putting Dify to work across their businesses.

What's Next

Enterprises will not build every agent in one place. We plan to help teams connect and manage agents across platforms, with greater visibility and control. We're also exploring how agents and people can work together more effectively in the same process. Our goal is to bring agents, existing systems, and people together in business processes that enterprises can govern and operate from end to end.

This is just the beginning.

Being named in the first Magic Quadrant for AI Agent Management Platforms reinforces our confidence in the path ahead. We'll keep moving forward, helping enterprises build, govern, and operate AI agents at scale.

Explore how can we help your teams build, govern, and operate agents at enterprise scale.

Gartner Attribution

Gartner, Magic Quadrant for AI Agent Management Platforms, Andrei Razvan Sachelarescu, Lucas Kobat, Gilbert van der Heiden, Max Goss, 27 October 2026 •

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