AI automation that does the work, not the demo
Every business now has someone saying “we should use AI.” The useful question is narrower: which hours of repetitive work can software take off your team this quarter, reliably, without babysitting? That's the work we do.
What you get
Where automation pays back first
- Lead handling — every enquiry answered, scored and routed in minutes, so the hot ones never wait behind the cold ones.
- Daily reporting — the morning numbers assembled and delivered before anyone logs in.
- Order and stock operations — channels kept in sync, exceptions flagged, reconciliations done nightly.
- Customer communication — order status, returns and routine questions handled instantly.
Start with the Scan.
One fixed-fee pass across the whole business — ₹75,000 + GST introductory, list ₹1,00,000 — with the findings ranked by what each one is worth. The fee credits in full against the two-month Deep Audit if you go deeper. Or tell the chat agent what's stuck; it reaches Ronnie directly.
See engagements & pricing →Common questions
What can realistically be automated in a small business?
Anything repetitive and rule-based: report building, order and stock updates, reconciliations, first-line customer replies, alerts when something goes wrong. Judgement work stays with people; the copying and pasting around it does not.
How do you decide what to automate first?
By payback. We price every manual task in hours and rupees a year, then rank them. The first thing automated should be the one that pays for itself soonest, which is rarely the one that annoys people most.
Will this replace our staff?
It usually removes the part of their job nobody wanted. The realistic outcome is the same team handling more, and stopping the errors that come from doing the same thing by hand a hundred times.
What happens if an automation breaks?
It alerts rather than fails silently, which is the whole design question. An automation nobody is watching is worse than the manual process it replaced.
In more detail
Business automation services, measured in hours
Automation is worth doing when you can say what it saves. We count the hours a task consumes today, what those hours cost, and what the automation costs to build and run. If the payback is not clear, it is not worth building, and we will say so.
Where AI genuinely helps, and where it does not
AI is good at reading messy text, drafting, classifying and summarising: the tasks that used to need a person purely because a computer could not read. It is poor at anything requiring accountability without review. The useful pattern is AI doing volume with a human checking, which is how we run our own work.