Some clients hand us a spec on day one. Some don't know what to build yet. Some have a pilot bleeding money. The phases are the same. The starting line moves.
We figure out where AI will actually move your numbers, and where it'll waste a quarter.
No frameworks, no maturity scores, no four-quadrant matrices that look smart in a slide deck. A short list of bets, ranked by ROI and effort, with the first two already scoped enough to start building. You leave with a roadmap you'd defend in front of your board.
Begin here if AI matters for your business and you don't yet know where to point it.
Book the audit →We pick the highest-leverage bet and ship it. Not a demo. The actual thing, in production, used by real people.
Most engagements live here. The pattern: tight scope, opinionated build, working software every week, a hard line between what's in v1 and what waits. By the end you have proof, not a deck about proof, that you can take to leadership and use to fund the next bet.
Begin here if you already know what to build. You don't need more discovery. You need a team that can ship.
Scope my V1 →Most AI pilots die on the way to production. We build the layer that keeps yours alive.
Evals to catch regressions before users do. Cost controls so the LLM bill doesn't double every quarter. Governance and audit trails for the people who'll ask. Reliability tuning for the load you actually have, not the load the demo had. The boring infrastructure nobody puts in a deck, and everybody depends on.
Begin here if your pilot works in the demo and breaks in production. Or works, but costs too much to scale.
Stabilize my pilot →Pick the phase you're in. We won't make you sit through the others.
A 1 to 2 week diagnostic that asks where AI will actually move your numbers. We interview your operators, audit your data, and look at workflows, infrastructure, team capability, and governance. You leave with a short list of bets ranked by ROI and effort, plus the first one scoped enough to start building. The output is a roadmap you can defend to leadership.
4 to 6 weeks to the first production milestone is typical for a quick-win scope. Larger scopes are estimated after the audit. Production means real users, not demo users. The cadence is weekly working software, with a hard line between v1 and what waits. By the end you have proof, not a deck about proof.
You move into the production phase: evals, governance, cost controls, and reliability tuning for your actual load. Some teams keep us on a monthly retainer. Others fund a scoped hardening sprint and then take operations in-house. Source code, infrastructure-as-code, and deployment pipelines live in your accounts and repos throughout, so handoff is a normal day, not a cliff.
You can start at any phase. If you already know what to build, the quick-win phase is often the right entry. If your pilot already shipped and the production work is what is missing, the production phase is the entry. The audit exists for teams who do not yet know where to point AI.
The same engineers who scope the work do the building. There is no senior-to-junior handoff between the discovery call and delivery, and no SDR funnel between you and the people writing the code. Founder Soumyo Dey is in the codebase. The team you talk to first is the team that ships.
We tell you on the call, before any contract is signed. Sometimes the audit concludes that a heuristic, a SQL query, or a forms cleanup will beat an LLM for the workflow you are looking at. Saying so upfront protects your budget and our reputation. Problem first, tool second is not a slogan.
Tell us where you are and what you need. We'll come back with a clear, honest plan within 48 hours.