Transform how your team builds software. Keep the factory.
We join your team and work on your product: training sessions, 1:1 coaching, and building a custom AI software factory together with your engineers on your own repos. Your real backlog ships through it while new habits take hold, carried by full change management. Your team owns the factory when we leave. No lock-in, no per-seat fees.
Scoped to your team and priorities. Book a scoping call, a senior engineer picks it up.
Already have an AI task force? See the Factory Accelerator →- Embedded
- A forward-deployed engineer inside your team
- Months
- We stay until the rough edges are gone
- Your repos
- Built where your team works
- You own it
- The factory stays when we leave
What we build, and you keep
The deliverable isn't code, it's the system that produces code. Everything below is deployed into your environment and owned by your team.
Your own software factory, on tools your team already uses
Built on common tools like Claude Code, plus the integrations and harness that turn them into a production line. Low risk, minimal lock-in, and yours.
A real assembly line for code
Planner, generator, and an independent reviewer that checks the work. Intent goes in, a spec comes out, code gets built, a second pass verifies it. You control each handoff.
Your context, written down as code
Your architecture, conventions, AGENTS.md and CLAUDE.md, versioned and reviewed in your own pull requests. Owned by named engineers, not locked in a vendor's account.
Quality gates and guardrails that hold the line
Automated checks for style, security, and correctness at every step, so speed doesn't cost you quality. The bottleneck today is review and QA, not typing. This is where the system does the most work.
Full visibility into what it ships and what it spends
Logs, traces, cost and token metering, drift alerts. You see what it ships and what it spends.
Your real backlog, shipped through it
We don't run a demo on toy problems. We run the engagement on your actual features. That's the proof, the tuning, and the ROI, all at once.
A team with new habits, and the skills to keep them
Training sessions and 1:1 coaching run alongside the build: a new mindset, new workflows, a new way of producing software. Full change management carries it, so the change lasts.
Embed, ship, own.
No sharp cutover at the end. Your team is operating the factory before the engineer leaves, because they helped build it on their own work. We stay until the rough edges are gone.
Phase 1
Embed & stand up
The engineer joins your team and stands up the factory on your repos.
- The forward-deployed engineer joins your team, your Slack, and your real repos, messy parts included
- The software factory stood up in your environment, on the tools your team already uses, wired to your repos
- First slice of your context encoded as code: architecture, conventions, AGENTS.md and CLAUDE.md, in your own pull requests
- A real backlog picked with you, no skunkworks, no toy problems
Phase 2
Ship & tune
Your real features ship through the factory while the factory gets built.
- Planner, generator, and independent reviewer profiles built and tuned against your actual SDLC
- Quality gates and guardrails for style, security, and correctness wired into each handoff
- Real backlog stories shipped through it, which is the proof, the tuning, and the ROI at once
- Observability in place: logs, traces, cost and token metering, drift alerts
- Training sessions and 1:1 coaching alongside the build, so skills grow with the factory
- Your engineers start directing the work instead of writing every line
Phase 3
Own & extend
Your team already runs the factory it helped build. We make ownership complete.
- Your team trained to run and extend the factory: new capabilities are new profiles, not new platforms
- The role shift made explicit: eval-first development, reshaped code review for AI-generated code
- Everything versioned in your repos, owned by named engineers, nothing in our accounts
- A board-ready final report: where your team was, where it is now, what it owns, and the baseline your KPIs are tracked against
- Optional Operating Partner afterwards, for continuity as models and tools shift. Never a dependency
"We save hours each sprint with dependable story refinements and test plans, without adding complexity to our workflow. Codeligence has been reliable and easy to work with."
Scoped to your team and priorities. Book a scoping call, a senior engineer picks it up.
Not a ticket queue. Not a slide deck.
Builds against your real work
The engineer sits with your team and works on your real repos and workflows, messy parts included. No clean room, no sandbox.
Ships your backlog through the factory
Production features go out while the factory gets built, so it's tuned to how you actually work, not how a demo pretends you do.
Trains your team to run it
The shift from writing every line to directing the work, eval-first development, and reshaped code review for AI-generated code.
We build the factory with your team, not for them. A factory the team helped build gets kept, and your engineers are running it long before we leave.
You own the factory, because you helped build it.
The reusable engine comes free. What makes the factory yours is the configuration, and it stays with you.
- 1 The configuration that makes the factory yours: your encoded context, profiles, evals, and guardrails
- 2 All of it living in your repos, versioned and reviewed by your own engineers
- 3 The right to change it, extend it, and keep running it long after we leave
- 4 Your team running it before we leave, no sharp cutover. The one limit: you can't resell it
What you're paying for.
You already carry the budget for one senior or AI-specialized engineer. This costs a fraction of that one hire over a year. The difference: that engineer leaves with one feature shipped. We leave a factory that multiplies the whole team, your team trained to run it, and your first real features already shipped through it. You're buying the machine, not the hours.
Book a scoping callScoped to your team and priorities. Book a scoping call, we take it from there.
The embed works because you meet us halfway.
Three commitments from your side. In the statement of work.
Pick the team and a real backlog
Real features, not a side project. The factory gets tuned on the work that actually matters to you.
Give access and protect the time
Repos, Slack, and the tools the work touches. Plus protected developer time for the training, so your people learn to run it, not just watch.
Show up at three checkpoints
Kickoff, mid-point, and the final report review. Your presence is what tells the team this matters.
Who the Factory Transformation is not for.
We only take engagements we can land. We decline or defer the build when:
-
You want a body to write code. This is a factory you keep and run, not staff augmentation. If you just need hands, hire a contractor.
-
You are mid-crunch or mid-reorg with no protected developer time. Nobody learns to run the factory while the building is on fire. We would rather start after your release.
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There is no CI and no code review culture, and test coverage is near zero. A factory on top of chaos ships chaos faster. The foundations come first.
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You want to enable your existing team without an embedded build. That is the Factory Accelerator, a workshop format where we configure your repo and train your team, in days to weeks depending on team size and project complexity.
Not sure the full build is the right move? The Factory Accelerator gets your team agentic-ready and your repo configured. A standalone path to the same destination.
What changes when the factory is yours.
"We were using Claude Code but treating each session as a one-off, with no shared conventions across the team. Now we approach it as an orchestration model, not a coding assistant. The goal shifted from AI helps us code faster to AI handles implementation while we supervise architecture and outcomes."
Bryan Scown
Director of Software Engineering, Valant
Questions CTOs ask before signing.
Why pay for this when a contractor could write the code? +
A contractor leaves with the work done once. We leave a factory that does it again and again, run by your team. You're paying for the machine, not the hours. The shipped features are just the proof it works.
What happens when your engineer leaves? Isn't that key-person risk? +
There's no sharp cutover. Your team is operating the factory before we go, and everything lives versioned in your repos, not in our heads or our accounts. If you want continuity as models and tools shift, there's an optional Operating Partner retainer. It's there for continuity, not dependency.
Is 'custom' just your open-source repo with a config file on top? +
No. The custom part is encoded inside your repos: your architecture, conventions, profiles, evals, and guardrails, reviewed in your own pull requests. It's configured for you, not bolted on. It doesn't walk out the door when we do.
We could just build this ourselves. +
That's exactly the goal. We're not here to be a permanent vendor. We accelerate it, de-risk it, and train your team to own and extend it. You end the engagement with the capability in-house, which is faster and cheaper than figuring it out from scratch while shipping your roadmap.
How do I prove the productivity gains to my board? +
We baseline first and measure against it, using DX Core 4 and DORA, and the measurement protocol is written into the contract. We don't publish productivity percentages until a case study backs them, so you get your own numbers from your own repos rather than a vendor's slide.
Transform how your team builds software. Keep the factory.
A short scoping call tells us whether the Factory Transformation is the right move for your team, and tells you exactly what the engagement would look like. Scoped to your team and priorities.
Already have an AI task force driving adoption? The Factory Accelerator may be the better fit.
See the Factory Accelerator →