Method
Diagnose. Deploy. Operate. Expand.
Four stages, in order. You can stop after any one of them, and it is always clear what happens next and who is doing it.
Diagnose
3–10 days · paid · credited
We map the workflow as it actually runs, quantify what the friction costs in rupees a year, and rank the opportunities on impact, feasibility and risk. You leave with a 90-day plan and a go / no-go — including, sometimes, “fix the process first”.
Deploy
4–12 weeks · fixed scope
Build, connect the real tools and the real data, add guardrails and escalation, test against your own historical cases rather than a demo set, train the team, hand over runbooks. Acceptance criteria agreed before we start.
Operate
Ongoing · this is the actual business
Monitoring, failure review, knowledge maintenance, evaluation runs, model and cost management. Most firms hand over a build and disappear. The value of an AI system is almost entirely in the months after launch, so that is the part we keep.
Expand
As patterns repeat
The second workflow is faster and cheaper than the first, because the controls, integrations and evaluation harness already exist. Patterns that repeat across clients become modules, and you benefit from every one we have already shipped.
Six things every deployment includes.
Not options. Not a governance package sold separately at the end.
A baseline before launch
We measure the current state first. Without it nobody can tell whether the system worked.
A named owner
One person at BYBO and one at your end. Not a shared inbox, not a ticket queue.
Approval where it matters
The routine runs unattended. Only the crucial calls — money, commitments, records — wait for a person you name.
Failure handling
Written before launch: what happens when it is unsure, wrong or offline, and who hears about it.
Cost visibility
What the system costs per month and per transaction, visible to you, not just to us.
Team training
The people working alongside it are trained on it, including on when to overrule it.
Versus a development agency
An agency finishes at handover. We start there.
A development shop is paid to ship a scope and leave. That model is fine for a website and fatal for an AI system, because an AI system degrades: the data drifts, the edge cases arrive, the model changes underneath you, the costs creep. Someone has to watch it, measure it and correct it every month. We would rather be paid for that than for the build.
Start with the stage that fits.
Most engagements begin with a Blueprint. If you already know the workflow and the number, we can go straight to a fixed-scope build.