Purchase entry in Tally
GST number27ABCDE1234F1Z5
Bills retyped into Tally, WhatsApp enquiries waiting until morning, calls nobody picks up, the report someone builds by hand every Monday. Tell us yours. We’ll build the software that does it, connect it to the systems you use, and test it on your own past work before it touches a live customer.
If someone in your team reads something, decides by rules they could explain to a new hire, and types the result into a system, we can build it. Here’s what we build. Pick what you need, or type it in.
Every one of these has the same four parts: what comes in, what the software does, who checks it, and where it ends up.
Example
A PDF, or a phone photo of a paper bill.
Reads supplier, GST number, items and total, then matches them to the purchase order.
Your accountant sees only the bills that don’t match.
The entry is ready in Tally, Zoho Books or QuickBooks with the bill attached.
Most aren’t. Tell us what your team does all day and we’ll say how we’d build it. If nobody can say how they decide, we’ll work that out with them first.
Tell us what to automateMost aren’t. Tell us what your team does all day and we’ll say how we’d build it. If nobody can say how they decide, we’ll work that out with them first.
Tell us what to automateNobody moves to a new system or learns another dashboard. We connect directly to any system that allows it. If a system only has a login screen, the software works that screen the way a person would, with an account limited to that work.
The bill is made up. The steps are what would happen.
A supplier emails a two-page PDF. The bill number is on page one and the total is on page two, because that’s how this supplier does it.
Supplier, GST number, line items, tax and total, each one marked on the page, so whoever checks it can see where a figure came from.
The GST number goes against your supplier list, the lines against the purchase order, the items against the total. Whatever matches carries on without anyone touching it.
The order said 40 cartons and the bill says 48. Your accountant gets one question with that line marked, opens the delivery note, and picks 48. The other lines need nothing from anyone.
With the PDF attached and a record of what was read, what was changed and who changed it. Your accountant touched one line out of a whole bill.
Try it. Anyone in your office can get a prototype answering questions with ChatGPT or a coding agent. It stalls the day a bill arrives sideways, two people get two different answers, nobody can see what was sent, or the monthly charge comes as a surprise. Here’s what you get from us.
It works inside the tools your team already opens every day.
It follows your prices, limits and approvals the same way on every item.
The AI that suits your job, changed whenever a better one comes out.
Your team sees the original beside the result, so checking takes seconds.
You see how it does on your own documents before it touches a customer.
What came in, what went out, who approved it and what it cost. If a provider goes down, nothing is lost.
Steado reads photos of meals and has a coach that updates a person’s plan when they ask, in English, Hindi or Hinglish. Maharaj answers restaurant owners’ questions about their sales in English, Hindi or Marathi.
Why did Tuesday’s sales fall?
Tuesday’s sales were ₹18,400 below the usual Tuesday, down 12%. Orders fell 9% and the average bill fell ₹42.
Sample data
Dinner changed to paneer bhurji.
Sample data
Refunds, legal replies, anything a customer will remember.
CRM fields, ticket labels, a change to a plan.
A bill that matches its purchase order to the rupee. A question your FAQ already answers.
Sample data
Every job starts on the first row and moves down once you’ve read enough of its record to be comfortable. It will get things wrong: it will misread a smudged bill, and now and then it will sound sure about a wrong answer. So we count how often that happens, and we count how long your people spend checking. If checking takes as long as the old work did, the job isn’t worth automating yet, and you’ll see that in the numbers before you pay for more.
You talk to an engineer. Afterwards you get a written answer: whether it fits, what we’d test first and roughly what it would take. Sometimes that answer is a setting in software you already own, and then we’re done. This part is free.
One job, a fixed price, your own documents. We write down the pass mark together before we start. You keep the code and the results, and you can stop there.
Connections, review screens, tests, records and handover. One lead stays with it from start to finish, and you get the source code at the end.
We take on a few builds at a time, from Mumbai, with teams in India, the UK, Europe and the US.
Often you can, to begin with. If someone pasting documents into ChatGPT or one Zapier rule does the job, keep it. Come to us when the answers stop agreeing, when nobody can see what was sent, or when the tool can’t reach the system that matters.
Sometimes. An agent works out its own next step, and we build those when a job needs one. Most office work runs better on fixed steps, because it costs less and its mistakes are easier to predict. Some suppliers call both of these agentic AI. Your written answer will say which one your job needs.
Before we build, you get a one-page map: which systems we read, which fields reach an AI provider, how long anything is kept and what’s never sent. We use provider settings that stop your data being kept or used for training. If it can’t leave your own systems, the AI runs on your cloud account or your own servers.
The first conversation and the written answer are free. The test is a fixed price, quoted once we’ve seen the job. With it you get an estimate of what each item will cost to process once it’s running, so whoever signs off the budget can check the sums first.
We agree a date for the test before it starts. The build depends on how many systems it touches, and you’ll have that date before you commit to it.
The item goes to a person with the doubtful part marked, and nothing is saved until they accept it. The mistake joins the past work we test against, so the next version has to get it right. For jobs that act alone, you set the limits, and you can move any job back to drafts.
You get the source code, deployment notes and documentation. IP and licences are set in the project agreement before work begins.
Yes. We build in Hindi, Marathi and Hinglish, and we test any other language on your own messages before it goes live.
Any business with people reading, typing and following up. Clinics, real estate, banks and NBFCs, insurance, retail, manufacturing, distribution, logistics, schools, law and CA firms, and software companies adding AI to their own products.
Yes. If something built with Cursor, Lovable, Bolt or Replit has reached its limit, we make it secure and stable, and rebuild the parts that can’t be saved.
Yes. We train staff on ChatGPT, Claude and Microsoft Copilot using their own work, and we set up the rules for what can and can’t go into those tools.
Yes. Most people start with one job, such as missed calls or supplier bills, and add more once it’s paying for itself.
Yes. We work from Mumbai with teams across India, the UK, Europe and the US.
A few lines is enough. An engineer reads it, and you get a written answer on whether it fits and what we’d test.