What working with us actually looks like.

• Production from week two. If it's not running with real users on real data, it's not an MVP. It's a prototype. Different word, different bar.
• Evals from day one. No model, prompt, or agent ships without an eval suite. The suite is the contract.
• Auditable reasoning. Every automated decision a regulator might ask about ships with a trace your compliance team can read.
• No black boxes. If your team can't run, debug, and extend the system after we leave, we haven't shipped. Every component is documented, instrumented, and replaceable.
• Human-in-the-loop where it matters. We are aggressive about automation and conservative about the cases where automation needs a person on the hook. The cases that need it are not the cases that look like they need it.

A use case is worth doing only when all three of these are true:

1. 1
   Business value is named, and you can measure it

   The use case moves a number the business already cares about — cost, revenue, cycle time, risk. Vague upside ("AI will help us be more efficient") fails this test.

2. 2
   The data and the access already exist

   The data you need is reachable in weeks, not quarters. If the answer is "we need a 12-month data project first," this is a data project, not an AI project.

3. 3
   A real operator wants to live with the system

   Someone whose day-to-day work changes wants this to succeed and will run it after handoff. Executive sponsorship without an operator owner does not survive the first month in production.

Two out of three doesn't ship. If your sponsor cares and the data is there but no operator on your team will own the system after handoff, it won't survive in production. If your operator wants it but the data is a year of integration work away from being usable, you have a data project on your hands — not an AI one. We'll tell you which one you have in week one, before either of us commits.

A pod is the smallest unit of our work. Every pod has:

• 1A strategist who owns the business outcome
• 2An industry expert who knows the workflow we're transforming
• 32–3 Frontier Engineers, mixed seniority
• 4A designer focused on the human side of the system
• 5A change lead so the new way of working actually sticks
• 6A senior partner on point for the engagement

Pods deploy in 2-week sprints. We co-locate with your team — physically when it helps, virtually when it doesn't. There is one bar for hiring; no offshore tier with a different one.

KPIs are defined in week two of every engagement, before we write a line of code. The MVP either hits them in production or it doesn't, and we report against them every two weeks.

We don't move the goal posts. We don't redefine the KPI when the numbers come in soft. A pod that misses its target is a pod that either re-scopes with the customer or hands the engagement back. Both options are on the table and both are honest outcomes.

When we hand off, we hand off a system, not a prototype. That means:

• Documentation your team can read — architecture, data contracts, deployment runbooks, eval criteria, the decisions we considered and the ones we made.
• Infrastructure your team can run — IaC, monitoring, rollback procedures, on-call playbooks.
• Evals your team can extend — we ship the eval harness, the prompts, the labelled fixtures, the regression suite.
• A lead architect from our side who stays in your Slack for at least 90 days after the handoff. Most stay longer because they want to.