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Services

Four services. One path from experiments to standard practice.

Most teams don’t need another tool. They need a foundation: a clear read on where they stand, standards the whole team shares, and AI built into the way they already deliver software. We work through it with you in four stages, and you can start where you are.

1 · Assess2 · Build AI Foundation3 · Optimize the SDLC4 · Orchestrate
Stage 1 · The front door

Assess

Know exactly where you stand before you invest.

We assess your code, your team, and your delivery process, then hand you a prioritized action plan for your AI foundation. Evidence first, decisions second.

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The problem

It’s hard to fund the next step when you can’t see the current one. Leadership wants a plan; the team wants it to be realistic. An honest baseline gives you both.

What we do
Assess Codebase. Your software inventory, what each system uses, its architecture, and the state of its testing, CI, and deployment.
Assess Team. Interviews across the team: what they’ve tried, what they liked and didn’t, and where they see real opportunities.
Assess SDLC. Are tickets good enough to build from? How good and how fast are code review and CI? How reliable is automated testing and deployment?
You get

A current-state report and a fundable, prioritized action plan — the AI context artifacts to build, training to level up the team, improvements to CI, review and testing, standardization decisions, and the metrics to track.

Stage 2 · The plateau to reach

Build AI Foundation

The standards, artifacts, and training that make AI stick.

We embed with your team to turn scattered experiments into a shared way of working, built with the people who’ll use it every day.

Build your foundation with us
The problem

Experiments don’t compound. Without shared standards and the right context in place, every engineer starts from scratch and good practice never spreads.

What we do
Train your people on how to use AI and when to avoid it.
Establish AI context artifacts for the standards you agree on — docs, agents.md, skills.md, and templates the team builds with us.
Set up a feedback loop so experimentation continues on top of the standard instead of around it.
Establish SDLC metrics so progress is visible.
You get

A team producing code with AI, faster and with better quality — a reusable library of standards and artifacts, experimentation that builds on a shared base, and metrics leadership can watch.

Stage 3 · AI-assisted engineers

Optimize the SDLC

AI across the whole lifecycle, not just the editor.

Once the foundation holds, we weave AI through design, build, and monitoring so delivery gets genuinely faster, with quality that holds up.

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The problem

AI in the editor helps one developer at a time. The bigger gains are across the whole loop: requirements, review, testing, and closing the loop from running software back to the start of the next cycle.

What we do
Design. AI-assisted requirements built on your established context artifacts, so tickets are good enough to build from.
Build. Your engineers, accelerated by AI. We build the code-review agents, CI improvements, and acceptance-testing harnesses that speed the work without taking people out of it.
Monitor. Once software is deployed, we watch how it runs and turn what we learn into tickets that re-enter the SDLC at the start.
You get

Faster design-to-delivery, higher review and test coverage with less toil, and a working feedback loop from production back to the start of the next cycle.

Stage 4 · The destination, your AI factory

Orchestrate

Orchestrated agents running your delivery line, with your people in command.

Once the SDLC is optimized and trusted, we hand well-scoped work to orchestrated multi-agent workflows. Your engineers direct and supervise; the agents take the toil.

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The problem

This is where most AI initiatives try to start, and it’s why they fail. A build without a foundation collapses. Orchestrated agents only pay off once the earlier stages are solid: reach this stage in order and it compounds; skip ahead and it comes down.

What we do
Stand up orchestrated workflows for the parts of delivery that are ready, one at a time.
Set the guardrails. Human checkpoints, review gates, and clear limits on what runs unattended.
Expand as trust grows. We widen agent coverage only as results and confidence earn it.
People in command

Agents handle the toil, not the judgment. People stay in the driving seat: directing the work, approving what ships, and deciding where agents belong and where they don’t.

Not sure which stage you’re at?

That’s what the assessment is for. We’ll map your current state and show you the fastest sensible next step.

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