AI CO-WORKERS, IN YOUR WORKSPACE

Bring AI into the places where work happens.

Curie brings AI agents into the workspaces your team already uses. Start with the Software Factory: turn selected engineering issues into reviewable pull requests while your team keeps the final say.

FIRST USE CASE: SOFTWARE FACTORY · OPEN SOURCE · SELF-HOSTED
ONE PLATFORM. MANY WORKSPACES.
GitHub · GitLab · Jira · Slack · Bitbucket
START HERE

Meet your Software Factory co-worker.

Put selected GitHub issues through a controlled workflow that plans, implements, checks, and returns a pull request for engineers to review.

Each issue runs in an isolated sandbox. Choose models for implementation and review, apply your approval policy before publication, and keep CI and engineers in charge of what merges.

SOFTWARE FACTORY WORKFLOW / 01
01
ISSUE
Pick a bounded task

Give the co-worker clear acceptance criteria in the issue tracker.

GitHub issue ↗
02
DELEGATE
Curie works in the background

Follow planning, implementation, review, and verification as work progresses.

03
REVIEW
Your team accepts the result

Inspect the pull request, checks, and cost before deciding what ships.

Pull request ready ✓
THE SHIFT

Agents are getting better. Their workspace is too small.

Most agents sit in a separate app. Your team works across issues, code, chat, and approvals. Curie connects the agent to that shared context, so work can move forward where the team already coordinates.

WHERE AGENTS OFTEN LIVE
IDE · Chat app · Agent workspace

Useful work, isolated from the team’s daily flow.

WHERE THE TEAM WORKS
Issue → Code → Thread → Approval

A co-worker with an identity and a place in the workflow.

01

Like a teammate

Delegate work, ask questions, and follow progress from the spaces you already use.

02

Visible to the team

Work and decisions stay in shared context instead of disappearing into a private session.

03

Under your control

Set model choices, approval boundaries, and budgets for the work you hand off.

WHY DEPLOY THE FACTORY

More reviewable work. Clearer economics.

The factory is designed to help engineering teams move a bounded issue queue while keeping cost and acceptance visible.

01 / COST

Spend the right model on the right work.

Configure implementation and review models independently. Use lower-cost models where they pass your checks, and stronger reasoning where it earns its cost.

02 / BACKLOG

Move selected issues into review.

Admit well-scoped issues with a GitHub label. Isolated jobs can progress in parallel and return a pull request or a clear reason they could not finish.

03 / ROI

Measure outcomes, not just tokens.

Compare accepted PRs, CI results, review effort, cycle time, and total model plus infrastructure cost. Engineers still decide what merges.

WORK WITH THE AGENTS YOU USE

Keep coding locally. Send queued work to the factory.

Use an IDE agent, Claude Code, or Gemini CLI for interactive exploration, issue scoping, and PR review. The factory picks up selected GitHub issues for independent execution. The shared handoff is the issue and the resulting pull request.

Explore the open-source factory ↗

01

Work locally with your preferred coding agent to investigate and define a bounded issue with acceptance criteria.

02

Apply the factory label to put that issue in the queue. Curie runs the job in an isolated sandbox.

03

Review the linked PR, checks, and cost in your normal GitHub workflow. Your team controls publication and merge.

THE PLATFORM

One co-worker platform. Built for real work.

The Software Factory is the first use case. The platform gives co-workers a shared foundation to run in your infrastructure and operate across workspaces.

02 / CONTEXT
Slack ↔ Code host

Context that travels

Shared memory facilities help the co-worker carry useful context across workspaces.

03 / CONTROL
Planning · Frontier model
→
Execution · Model of choice

Spend with intent

Configure models and inspect usage, with approvals and cost controls close to the work.

OWN YOUR CO-WORKER

Open source. On your infrastructure.

Curie is Apache 2.0 licensed and self-hostable. Start with the Software Factory, inspect how it works, and build from there.

✓ Apache 2.0 ✓ Self-hosted ✓ Your model configuration
Explore Curie on GitHub ↗
WORK WITH CURIE

Start with the platform. Go further together.

Adopt the open-source platform on your own, or work with CurieTech on a production rollout and a broader AI transformation program.

01

Explore

Try the open-source platform and prove out a bounded workflow.

02

Deploy

Get support for a production setup and the controls your team needs.

03

Expand

Bring more agents and workflows into the places your teams work.

THE FUTURE OF WORK, TOGETHER

Put your next AI co-worker where your team is.

See the Software Factory in action or talk through a co-worker for your team.