AI Engineering
Ecommerce Engineering
Product Engineering
Product Design
Platform & Integrations
Managed EngineeringYou Talk To The Engineer Who Writes The Code.
No account managers and no discovery theater. Eight stages, each with a fixed exit condition, a named engineer, and an artifact you keep whether or not we continue.
years in the industry, from startups to enterprise.
projects since 2016.
Upwork Job Success.
on Google.
A Process Built Around Decisions, Not Dependencies
A clear, staged path from first conversation to launch and beyond. Every stage stands on its own, with a useful artifact, decision, or recommendation you can take away. Move forward when it makes sense, or stop when you have what you need.
Discovery Call
Thirty minutes with an engineer who has shipped your exact problem before. We read your repo or staging URL first, so the call starts at the constraint, not at “tell us about your business.” If it isn’t a fit (wrong stack, wrong stage, wrong budget), you get told on the call, with a referral where we have one.
Technical Read-Through
Before anyone quotes a number, an engineer reads the codebase properly: dependency ages, extension conflicts, migration state, test coverage, deploy path, and the three files everyone on your team is scared to touch. On greenfield work this stage becomes a constraints review instead: traffic, compliance, integrations, and what the platform decision locks you into.
Scoped Estimate
We write the statement of work ourselves, not from a template filled in by someone who wasn’t on the call. Line items are priced individually so you can cut one without renegotiating the whole engagement. Where an estimate is genuinely uncertain, it is marked uncertain and time-boxed as a spike instead of padded.
Foundations Week
Environments, pipeline, staging, monitoring, and access, done once and properly before feature work starts. The first pull request lands in your repository this week even if all it does is wire up CI. This is also where the quality gates get their numbers: coverage targets, performance budget, and the definition of a red build.
We Tell You Where A Machine Helped
We use AI tools for parts of our work: converting old code, writing tests, first drafts of documents. It never reaches your system unlabeled, and a named engineer checks it and takes responsibility for it.
- Every batch of work says which files had AI help and which tool produced the draft.
- Your code, passwords and customer data never go into an AI tool without your permission.
- AI-written code passes exactly the same tests and reviews as anything written by hand. No shortcuts because it was quick and productive.
- If you would rather we did not use AI at all, tell us while we are writing the plan and we will price the work without it.
Four Principles We Work By
The standards behind every project, from the first call to year five.
One named engineer
The engineer who scopes your project builds it, and you can reach them directly. A backup engineer knows the codebase too.
Working software every week
You see the product running each week, so problems surface while they are still cheap to fix.
Everything in writing
Scope, response times and decisions are written down and shared, so nobody has to rely on memory when something changes.
The same team for years
We keep the same engineers on an account for years, so the people fixing an issue are the people who built the feature.
The Questions People Actually Ask
Talk to the practice, not a sales queue.
30 minutes with an engineer who has shipped this exact problem before.