Scale AI agents in production with the control, visibility, and repeatability your enterprise needs.
From the policies that govern how agents run, to the automations that trigger them, OpenHands Enterprise gives you control at every layer.
Wire OpenHands to GitHub, Slack, Jira, or a cron schedule. When the trigger fires, the agent runs in an isolated cloud container, does the work, and opens a pull request. You review the output.
Every token is tied to a user, session, repo, and workflow. Set budgets by project. See which use cases deliver ROl and which don't.
Define exactly which secrets, tools, and domains each agent can reach. Detect prompt injection. Halt risky actions for human review.
Track success metrics for any workflow. See which agents are delivering, where suggestions get rejected, and how to improve over time.
Platform, security, and finance teams all need different windows into what agents are doing. OpenHands gives them that, without requiring developer tooling access.
Wire OpenHands to the tools your team already uses. When something happens, the right agent fires, does the work, and opens a pull request.
Every automated run is fully logged and governed by the same cost and security policies as manual sessions. Automation doesn’t mean unsupervised.
“OpenHands was the only solution that let us prompt an autonomous coding agent remotely at scale — not just on a laptop or inside a narrow CI template.”
Sina Pakazad, VP of Data Science at C3.ai
Self-hosted in your VPC via Kubernetes. Source-available. Backed by extended support and direct access to our research team.
Deploy on your own Kubernetes infrastructure. Your code never leaves your environment. No shared tenancy.
Inspect all the code. Every capability and integration is readable and auditable by your security team.
Enterprise contracts include direct access to the team building the models. Not just support tickets.
GitHub, GitLab, Slack, Jira, and Linear out of the box. RBAC, multi- user support, and conversation sharing built in.
Model-agnostic by design. Use Anthropic, OpenAl, Bedrock, or any other model provider your team prefers.
Legacy modernization projects fail 74% of the time and the engineers who understand your COBOL, mainframe, and legacy systems are retiring faster than you can replace them.
_1.svg)
The teams shipping the most are moving beyond individual agent sessions to governed, automated workflows. Let us show you what that looks like in practice.
