AI consulting questions, answered plainly

An assessment runs two to three weeks and ends with a ranked roadmap. A pilot that takes one use case to production typically takes four to eight weeks. Scaling work continues in two-week iterations for as long as it earns its keep.

A lead engineer plus one or two senior engineers. The people on the kickoff call write the code. We do not hand off to a separate delivery team.

The assessment is fixed scope and fixed price, agreed up front. Pilot and scale work is quoted per milestone or on a time-and-materials basis with a weekly cap, whichever fits your budgeting. No retainer is required to start or to stop.

Work runs in your cloud project under your identity provider, logging, and access controls. Model and prompt choices are reviewed for data-handling implications before anything reaches production, and every decision is documented so your team can defend it later.

The engineers on the kickoff call write the code, and your engineers pair with them, so you are not dependent on us afterwards. If you can hire the team you need in the time you have, do that; the assessment will say so.

Access to the systems the work depends on, a named person who would use the result, and someone who can decide security questions. Without these the work slows down, and we will tell you.

Code, infrastructure, and docs have been yours from day one, so nothing transfers at the end. You can run it yourselves or ask for further two-week iterations. Neither is required.

Then the assessment is the right first step. Part of its job is to say no to use cases that will not pay off, and we will tell you if a conventional solution is the better fit.

A ranked roadmap of use cases with effort and risk per item, a readiness review of your data, security, and team skills, and a recommendation on what to build first, or a written no. It is fixed price and takes two to three weeks.

Yes. Code, infrastructure, prompts, and evaluation suites live in your repositories and your Google Cloud project from the first commit. Nothing transfers at the end because nothing ever left.

Whatever fits the use case and your constraints. We work with hosted model APIs and Vertex AI, and we choose retrieval, tools, and guardrails per use case, with an evaluation suite that shows the difference.

Yes. We take a clearly scoped product line or platform piece, pair with your engineers in the same repositories, and leave code, tests, and docs they already understand.

Per milestone, or time and materials with a weekly cap, whichever fits your budgeting. Scope is written down before work starts and reviewed at every two-week demo.

TypeScript across the board, React or Astro on the web, React Native or native on mobile, Node or Go services, Postgres, and Google Cloud or Firebase for hosting and data.

Platform work is Google Cloud and Firebase. If your data and systems are elsewhere and cannot move, the assessment will say so before anyone commits to a build.

What exists today, who can operate it, what it costs, and where AI or product work is blocked. It ends with the smallest platform design that removes the blockers, as infrastructure as code.

Your platform owners. Handover sessions, Terraform, runbooks, and dashboards are part of the build, and the work is in your project under your identity provider from day one.