A software factory, run for you. Agents on the line, engineers on the gate.
An AI software factory is an operating model where agents carry out the discrete steps of delivery — requirements analysis, planning, coding, review, testing and security scanning — while people specify the work and approve the results. We run that model for you. A SpurTree team takes your roadmap through ADIS end to end, and you get reviewed pull requests, test evidence and a traceable record of every decision.
You're in the right place if…
- Product companies that want to ship a roadmap without building and managing a large in-house team
- Engineering leaders who want AI across the whole delivery lifecycle, not only in developers' editors
- CTOs who need every change to be traceable back to an approved requirement
- Organisations that want to try an AI software factory on real work before changing their own process
What gets in the way.
AI gains stop at the pull request
Agentic coding tools turn a ticket into code, but requirements, design approval, testing and security still run the old way around them.
No record of why code exists
Once an editor session closes, the reasoning behind AI-generated code is gone. Three years later nobody knows which requirement it served.
Speed without control
Leaders want faster delivery but cannot accept unreviewed changes reaching production or code that ignores their standards.
AI Software Factory, end to end.
Requirement to reviewed diff
Your requirements are captured, refined and approved, then routed by the ADIS Orchestrator through BA, discovery, impact and coder agents to a pull request our engineers review.
Architecture before build
Each requirement is mapped to the components, services and data it touches, and a technical architect signs off the approach before code is generated.
Built-in testing and security
Test cases are generated from acceptance criteria, and OpenGrep, SonarQube and CodeQL run automatically, so evidence accumulates with the code.
Pre-review verification
Before a reviewer sees a change, it has passed compile verification, static analysis, secrets scanning and smoke tests in an isolated environment.
Traceability and reporting
The ADIS traceability grid links each requirement to its design, code, tests and security findings, and token cost is reported per change.
A delivery approach you can plan around.
Discover
We connect your repositories and let discovery agents index them, so plans are grounded in the code you actually have.
Define
We agree the roadmap, coding standards and approval gates with you, and set them up per environment.
Deliver
Requirements flow through the factory. Our team approves plans and reviews every diff before it merges into your repository.
Report
You see delivery status, test evidence, security findings and cost per change, without waiting for a stand-up.
Ways to work with us.
Pilot
One project, scoped tightly and run through your own approval gates, measured against your existing delivery baseline.
spurtree POD
A dedicated SpurTree team runs your roadmap through ADIS across all seven stages, scoped to your priorities.
Technologies we work with
- ADIS
- Jira
- Azure DevOps
- OpenGrep
- SonarQube
- CodeQL
AI Software Factory: common questions.
What exactly do we receive?
Pull requests in your repositories, requirements synchronised to your tracker, test suites and security findings, and exportable reports. If you stop, you keep all of it.
Who reviews the AI-generated code?
SpurTree engineers review and approve every plan and pull request, and your team can be added to any gate. Nothing merges without a human sign-off.
Will the code follow our standards?
Yes. ADIS generates against your coding standards and enforces them on every change, and plans are grounded in your actual repository.
Can we start small?
Yes. A typical pilot covers one project over 30 days, running through your own approval gates. We scope it with you before anything starts.
Let's talk about your ai software factory needs.
We'll reply within one business day with demo slots, and ask a couple of questions so the demo uses a scenario close to yours.