AI-integrated development that fits your environment.

Governed AI software delivery for ambitious small & mid-market companies - built on evidence, not demos. Generic AI meets generic environments. Yours isn't generic. We integrate AI into real production work the way it actually has to run: inside your architecture, your constraints, and your team's standards.

Talk to us about your environment

Your leadership is asking what you're doing about AI

Most answers right now are either too vague to act on or too aggressive to trust. The firms that will have a real advantage from AI-integrated development aren't the ones that adopted the tools earliest - they're the ones that learned how to govern them, and how to make them work inside specific client environments.

Four principles that separate governed work from generic AI claims.

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    Right Tool, Right Codebase

    Right Tool, Right Codebase

    Greenfield and brownfield are different problems. New builds use Spec-Kit, bMad, and GSD to translate intent into reviewable output. Established codebases start with codified context files - infrastructure on par with CI/CD - plus a custom process turned to the codebase.

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    Engineers in the Loop

    Engineers in the Loop

    Experienced engineers review every output. AI-generated code can compile, pass tests, and still be wrong for your system. Catching that takes engineers who understand your architecture and business logic. We don't skip that step.

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    Organizational Readiness

    Organizational Readiness

    Not just technical readiness. AI is a magnifying glass, not a fix-all. When generation speeds up but release processes don't, the bottleneck just moves downstream. We surface those gaps early.

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    Frameworks & Foundations

    Frameworks & Foundations

    Not just tools. We work across Claude Code, Cursor, GitHub Copilot, and OpenAI Codex - and know where each earns its place. Plus production-like local envs, adversarial agent testing, trunk-based dev, and a single agent "constitution."

Evidence, Not DemosWe're doing this live. Here's what we've learned.

  • 1.5M

    Lines of code. Brownfield system actively under management.

  • SDLC

    End-to-end. A full production build using agentic workflows across the lifecycle.

  • 5+

    Metrics tracked. Cycle time • defect rate • rework • integration quality • DX.

Start with a scoped management. Build from evidence.

Two ways to start.

Let's Explore What's Possible.
Let's talk about what this looks like in your environment.