Why not just hire someone?
Because that person barely exists. Someone who has practiced law and can also build with AI is rare, expensive, and already employed. Even if you land one, they take months to become productive and they leave with everything in their head. We apply the same expertise to your highest-value work now, and deliberately leave the specs, the systems and trained people behind.
We already bought an AI tool. How is this different?
A tool sits idle until someone redesigns the work around it, sets the review standards, and gets the team to trust it. That is the work here, and it starts from what you already own rather than selling you another license. Part of the honest answer to "should we build this" is often "no, configure the thing you already bought properly." Setup and Build Days exists for exactly that case.
Is this consulting, or a dev shop?
Neither, and that is the point. A consultant produces a recommendation and leaves. A dev shop builds exactly what you specify, including when the spec is wrong. We produce the spec, build the first working version with your team, then stay in the room while engineers scale it, so the intent survives all the way to production.
Why not hire an offshore development team for less?
Yes, and sometimes you should. If you already know exactly what to build, have a defensible specification, understand the legal risks, have an accountable owner, and have a plan for adoption and ROI, hire the development team. Excellent developers can build the app, and we are happy to work with yours. We are expensive when the problem is merely coding. We are valuable when those things do not yet exist. Most of the sprint is the work around the code: selecting and pricing the right workflow, translating legal judgment, redesigning the process, setting human review and escalation, leading change management, training the people who will use it, measuring adoption and return, and staying with engineering so the intent survives production.
When does the training happen?
Throughout, never at the end. Your people build alongside us from the first pavilion, on their own live work. Build days are run like a hackathon: the team arrives with real problems and leaves with something that works, plus a written spec for the next build. Training at the end of a project teaches people about a thing that is already finished.
What if the MVP shows the idea does not work?
Then you found out in weeks for a five-figure sum instead of in a year for a seven-figure one, and you still keep the method, the trained team, and a ranked list of the next candidates. Killing an idea cheaply is one of the most valuable things we do.
How do you prove the return?
We measure the baseline before anything changes, which is the step almost everyone skips and the reason most AI programs cannot prove anything afterwards. Then adoption gets tracked rather than assumed, and the cost to run gets set against the value returned. If it is not positive, that is a finding, and we say so.
Who owns what gets built?
You do. The specs, the workflows, the Skills, the playbooks, the prototypes, the trained champions. The engagement is designed to make itself unnecessary, which only works if everything it produces stays with you.
Does this work if our security posture is strict?
Yes, and it is usually the first constraint mapped rather than the last. Builds happen inside whatever boundary you set. Where something genuinely needs security review, data architecture or production engineering, it gets scoped explicitly and specialists get brought in rather than improvised around.
