Agent orchestration for enterprise engineering
Run coding agents inside your own perimeter.
Themis turns your backlog into governed agent work. It runs on your infrastructure, sends inference to your own Azure AI Foundry deployment (AWS Bedrock is next), works with any git repository it can clone, including self-hosted, and puts a person's approval on every merge.
The problem, in two parts
Enterprises bought the agents. The delivery never followed.
Agents run, but not as a team
Your developers can already point Claude Code, the Codex CLI or Copilot at your own Foundry or Bedrock deployment. What they don't get is the team layer: an isolated sandbox per task inside your network, one backlog across repositories, and a named approver on every change. The team-scale agents on the market run in the vendor's cloud, so inside your perimeter that layer is yours to build.
Access is solved. Outcomes are not.
Agent access went mainstream, but the gains cluster in a handful of power users. Real leverage now means authoring agents, skills and plugins — platform engineering, not application development. Most enterprise developers will never climb that second step.
Why you need it
What Themis actually solves.
Five things stand between an enterprise and useful agent delivery. Each one is closed by something specific — a capability, a control, or where the software runs.
You bought the agents. Only the power users got faster.
Closed by the interfaceA task board instead of a terminal. Developers file a task and review a diff — no prompts, no sessions, no CLI. The skill ceiling drops to things every developer already does.
Getting real value now means authoring agents, skills and plugins.
Closed by a built-in registryReview agents, security checks, reusable skills and task templates ship with the product and are enabled centrally. Your best engineer authors once; everyone else just gets the result.
The agents that work a backlog run in the vendor's cloud, not yours.
Closed by where it runsThemis runs inside your own network, against any git repository it can clone and push to, whether that's GitHub Enterprise Server, GitLab Self-Managed, Bitbucket Data Center or cloud git. Inference goes to your own Azure AI Foundry deployment under your IAM, with AWS Bedrock next. Nothing leaves the perimeter.
Security has to say yes before any of it ships.
Closed by the governance modelA person approves every merge. Per-task isolation, branch allowlists, API keys scoped per user and team, and a full audit trail of every run and decision. The artifacts a vendor-security questionnaire actually asks for.
Leadership needs proof the AI spend is working.
Closed by measurementTokens, cost, tasks merged and review outcomes, broken out by user, workspace and model. Productivity measured at the merge, not the keystroke.
What it is
A task board, not a terminal.
Nobody writes a prompt. Nobody authors an agent. Developers file work and review results — the two things they already do every day. Themis does the planning, the isolation and the bookkeeping in between.
- 01
Describe the work
A feature in plain language, or a ticket from Linear. Themis drafts the spec and decomposes it into sized tasks with priorities and dependencies — and a lead approves the plan before anything runs.
- 02
Agents execute in isolation
Each task gets its own git workspace cloned from your repository, so parallel agents never collide. Inference goes to your endpoint under your own IAM, and branch allowlists bound what any agent can touch.
- 03
Automated review runs first
QA and security agents check every change before a person looks at it, with full transcripts and run logs. One-click environments bring the change up so reviewers try it live rather than reading a diff.
- 04
A human owns the merge
Accept, edit or revert each individual change. Every run, decision and merge lands in an audit trail your security team can actually read.
Why it fits an enterprise with a perimeter
The model layer is solved. The team layer is not.
Every frontier model is already privately deployable, in your own cloud account and region, with no training on your data. The agents are solved too: Claude Code, the Codex CLI and Copilot with its own key all run against that deployment. What's missing is the layer above them: running agents as a team, inside your network, with a person approving every change.
The whole system runs in your account
Orchestrator, task workspaces and inference alike run on your own VM or cloud account. There is no control plane we operate and no data plane we can see. AWS and Azure Marketplace listings are on the way.
Your models, your keys, your contracts
Azure OpenAI and Azure AI Foundry today, under your IAM; AWS Bedrock is next. Model data handling stays governed by the cloud agreement you already signed, not a new one with us.
The git you actually run
Themis works at the git level, so self-hosted estates are first-class: GitHub Enterprise Server, GitLab Self-Managed and Bitbucket Data Center, alongside cloud git.
Governance a security committee can read
A human approves every merge, every run is recorded end to end, branch allowlists bound what agents can reach, and API keys are scoped per user, workspace and team.
The practical effect on a review: one vendor, one registrable ICT third party under DORA, and no access to your data plane.
Proof
Themis is built by Themis.
Every release of this product ships through its own agent fleet, and the figures below are reconstructable from our git history rather than asserted. The review gate held for all of it.
Internal use on our own codebase. Commit volume is a throughput measure, not a productivity metric.
Private beta
We are onboarding a small number of design partners.
If you run an engineering estate where AI has to stay inside the network — financial services, pharma, defence, insurance, or any Fortune 500 platform team — we would like to talk.
Or email us directly at beta@getthemis.ai