From agents to systems
Scale AI agents in production with the control, visibility, and repeatability your enterprise needs.
A control plane for every layer of your agent stack
From the policies that govern how agents run, to the automations that trigger them, OpenHands Enterprise gives you control at every layer.
Everything you need to govern agents in production.
Agents that run themselves, on your terms.
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.
- Trigger from GitHub issues, Slack messages, Jira tickets, or a schedule
- Every run is logged, attributed, and governed by your cost and security policies
- Cloud-native runtime — no agent running on a developer's laptop
Know where every token goes
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.
- Per-session tracking with custom labels
- Budget limits by project or team
- LLM routing to optimize cost vs. quality
Agents get access to what they need. Nothing more.
Define exactly which secrets, tools, and domains each agent can reach. Detect prompt injection. Halt risky actions for human review.
- Containerized sandbox runtime for safe autonomy
- Prompt injection detection with automatic halt
- Complete audit logs for every agent action
Measure what's working. Improve what isn't.
Track success metrics for any workflow. See which agents are delivering, where suggestions get rejected, and how to improve over time.
- Custom metrics per skill or workflow
- Track merge rates and suggestion acceptance
- Built-in feedback loop from production
One view for every team.
Platform, security, and finance teams all need different windows into what agents are doing. OpenHands gives them that, without requiring developer tooling access.
- Fine-grained access control and RBAC
- Org-wide policy enforcement
- Single pane of glass across all workflows
From event to PR, no human in the loop.
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
Built for teams running agents at scale.
Self-hosted in your VPC via Kubernetes. Source-available. Backed by extended support and direct access to our research team.
Self-hosted in your VPC
Deploy on your own Kubernetes infrastructure. Your code never leaves your environment. No shared tenancy.
Source-available
Inspect all the code. Every capability and integration is readable and auditable by your security team.
Research team access
Enterprise contracts include direct access to the team building the models. Not just support tickets.
Enterprise integrations included
GitHub, GitLab, Slack, Jira, and Linear out of the box. RBAC, multi- user support, and conversation sharing built in.
Bring your own LLM
Model-agnostic by design. Use Anthropic, OpenAl, Bedrock, or any other model provider your team prefers.
Whitepaper: Modernize legacy systems before your expertise disappears
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.
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.
