Approach

How we engage on AI builds

We don't do fixed-scope on AI work. AI projects are research projects — research with a fixed scope produces fixed-scope output, not the right answer. Here is how we engage instead.

Engagement models

Three ways to work with us

Discovery Sprint

$25–40k

2 weeks

Build-vs-buy decision, technical roadmap, scoped POC plan

ForTeams that need clarity before committing to a multi-month build.

Build Engagement

$80–250k+

8–16 weeks

Shipped product, integration, or agent system

ForTeams ready to invest in custom AI infrastructure they own.

Embedded Retainer

$20–35k / month

Ongoing

Continuous AI capability embedded with your product team

ForTeams with sustained AI build needs and no in-house specialist.

Weekly rhythm

What a week looks like inside a Build engagement

  1. Mon

    30-minute planning sync

    We confirm the week's goal and surface any blocker we need from your team.

  2. Tue–Thu

    Heads-down build + async updates

    Continuous Slack updates with code links and short Looms — no status meetings.

  3. Fri

    Working demo + decisions log

    A real demo against real data, plus a one-pager of what shipped and what we need next.

  4. Every 2 weeks

    Eval review + roadmap recheck

    We re-run the eval suite, decide what stays in scope, and confirm or adjust the remaining timeline.

What we believe

Five non-negotiables

  • We build evals before features.

    Models that ship without measurable evaluations fail silently in production. We define the metrics that matter before we write the prompt, and we keep them as the contract for what done looks like.

  • We require real production data access in week 1 — or we do not take the engagement.

    Synthetic data tells you nothing useful about an AI system. If we cannot read the actual data the model will operate on, we cannot honestly scope, estimate, or evaluate the build.

  • We ship a working POC by week 4 — or we restructure the engagement.

    If we cannot get a functional proof of concept in front of you by week 4, the scope is wrong and we are pretending. We stop, restructure, and refund the difference rather than spend the next 12 weeks finishing a thing that should not exist.

  • We do not do fixed-scope on AI work.

    AI projects are research projects, and research with a fixed scope produces fixed-scope output — not the right answer. We engage in time-boxed cycles with clear go / no-go gates instead.

  • You own the code, the models, and the data integration.

    No vendor lock-in, no proprietary runtime, no "open core" surprise. We hand off complete codebases with deployment runbooks and the eval suite that proves it works.

Artifacts

What you actually receive

Roadmap

Discovery brief

A scoped roadmap with build-vs-buy reasoning and a recommended POC plan, delivered end of Discovery.

Architecture sketch

Component diagram + data-flow notes for the system we are proposing to build. Shipped before any production code.

Evals

Eval suite

The set of test cases we measure the model against — and the score thresholds that gate every release.

Weekly demo + decisions log

Every Friday: a 20-minute working demo, a one-page summary of what shipped, and the decisions we need from you next week.

Want to start with a Discovery sprint?

Two weeks, scoped POC + roadmap, full pricing transparency. Book a discovery call and we'll figure out if it's the right shape together.

Book a discovery call