Secure, govern and scale AI-powered software development.
Accelerate delivery across a large organization while keeping visibility and operational control.
Large organizations often struggle with
- AI adoption without governance
- Multiple teams working in silos
- Inconsistent delivery processes
- Knowledge scattered across tools
- Security requirements on every change
What AI agents change for an enterprise
In a large organization the question is rarely whether a team can use AI; it is whether the company can answer for it afterwards. Tools arrive team by team, each with its own account, its own data path and its own idea of what an agent may touch. By the time the security review asks who approved a change, the answer lives in someone's chat history — if it exists at all.
Hive Teams makes the answer structural. Every agent has an identity and a scope, every run is a recorded session, and production, migration and secret work stop at a gate until the owner approves it on the work item. Session records can be exported over an API to your SIEM, so an audit reads the same story your board does.
Three situations enterprise teams bring to us
- 01Rolling agents out to three business unitsOne organization, a project per unit, the same gates everywhere. People sign in with Microsoft Entra ID; each unit sees its own boards.
- 02A security review asks who approved a production changeThe owner's approval is quoted on the work item with name and time, next to the session record and the DRAFT pull request it unlocked.
- 03A paid pilot before any wider decisionOne team, one epic, 30 days, measured on your own baseline. A plain list of what exists today and what is coming.
Scale AI with confidence.
See how one of your teams would run on Hive Teams, with the gates and records your security review will ask for.