Software companies need to deliver features faster, keep their platform healthy and add AI to their product — usually all at once. We provide product engineering capacity, modernise ageing platforms and bring AI-native delivery to the way software gets built.
Customer commitments outrun the team's ability to deliver, and hiring is slow.
An older architecture makes each new feature harder and each release riskier.
Adding AI features responsibly needs skills, architecture and guardrails the team may not have yet.
Leaders struggle to trace requirements through to code, tests and releases across teams and tools.
Illustrative scenarios showing how our capabilities apply — talk to us about yours.
The problem. The roadmap needs more capacity than the in-house team can provide, without the overhead of building a new team.
Our approach. Add a cross-functional pod that works inside your process and tooling, using AI-assisted delivery to move from requirements to tested code with human review at each gate.
The problem. A monolith or ageing stack is slowing feature delivery and raising hosting costs.
Our approach. Assess the codebase, agree target architecture, and modernise incrementally — with AI-assisted code analysis and regression testing so customers are not disrupted.
The problem. Customers want assistants, summaries or automation in the product, and the team needs to ship them safely.
Our approach. Identify the features with clear user value, build them on a sound retrieval and evaluation architecture, and add usage limits, monitoring and guardrails.
The problem. Engineering leaders want to use AI across the lifecycle, not just in the editor, without losing quality or traceability.
Our approach. Introduce an AI software factory that covers requirements, design, build, test and maintenance, with human approval gates and a traceability grid linking requirements to code and tests.
A dedicated SpurTree team — a spurtree POD — running your roadmap through ADIS, every stage, every week.
End-to-end software delivery run by a SpurTree team through ADIS agents — from first requirement to reviewed release.
Assess legacy applications, modernise their architecture and migrate them in stages — without a big-bang rewrite.
Code analysis, impact assessment, refactoring and technical debt management — grounded in an AI-indexed model of your real codebase.
Yes. Pods work in your repositories, ticketing and release process. ADIS can sync with Jira or Azure DevOps so work stays visible where your team already tracks it.
You do. Ownership and IP terms are set out in the contract before work starts.
No. ADIS is how we deliver efficiently, but we can work entirely within your existing toolchain if that suits you better.
Tell us the problem you're working on. We'll come back within one business day with how we'd approach it.