AI document processing
Somebody in your office is typing information off paper into software right now. AI document processing reads the PDF or the photo, pulls out the fields, checks them against what is already in your system, and flags only the lines that do not agree. A person reviews the exceptions instead of typing everything.
Is this you?
- Two people spend most of the month entering supplier invoices into Tally.
- Every supplier’s invoice looks different, so template-based tools keep breaking.
- Purchase orders and invoices are reconciled by eye, and the mismatches surface at audit.
- KYC documents are collected, scanned, and then typed in again by hand.
- Data entry errors are found weeks later, in the accounts, by an angry supplier.
What we build
- Supplier invoices, purchase orders, GRNs, delivery challans and e-way bills
- Bank statements, cheques and payment advices
- KYC sets — PAN, Aadhaar, GST certificates, cancelled cheques, incorporation documents
- Lab reports, prescriptions, test results and discharge summaries
- Contracts and agreements — key terms, dates, values and renewal clauses
- Three-way matching against POs and GRNs, with mismatches flagged rather than guessed
- Direct posting into Tally, Busy, your ERP or your own database
- A review queue for anything below a confidence threshold you set
What this is not
This is not simple OCR that reads a fixed template and falls over when a supplier changes their invoice layout. It reads documents it has not seen before, and tells you when it is not sure.
Any business handling more than roughly a hundred documents a month: manufacturers, distributors, contractors, hospitals and diagnostics, NBFCs, logistics companies.
- A written scope you approve before any code is written
- A price agreed against that scope, not discovered later
- Source code, database, documentation and IP yours on final payment
- Training for your team, and close support through the first month
AI software development
AI built into the system you already run, doing work your team currently does by hand.
Accounting and billing
Invoicing, receivables, GST and reporting, wired into the rest of your operations.
Integrations and APIs
Making Tally, your CRM, your website and your payment gateway talk to each other.
Questions people ask about this
How accurate is it, and what happens when it gets something wrong?
Nobody honest will quote you a single accuracy figure before seeing your actual documents and data. What we do instead is measure it on your real material during a pilot, and tell you the number we got.
The design matters more than the number. Every system we build sets a confidence threshold: anything below it goes to a review queue for a person rather than being posted silently. Anything touching money gets checked. You will always be able to see what the system decided, what it was unsure about, and what a person changed.
Where does our data go when you process it with AI?
AI processing is performed through OpenAI’s API. Your data is sent to that API for the specific task, and the result comes back into your system.
Before any project involving your data begins, we confirm the current provider data-handling terms in writing — retention, whether anything may be used for model training, and where processing takes place — so that it forms part of your agreement rather than an assurance in a sales call. If those terms do not work for your business, the honest answer is that this is not the right project for you, and we will say so at that stage rather than later.
Can the AI run entirely on our own servers?
Not today. Our AI work runs through a hosted API, so the processing happens outside your infrastructure even when the rest of the system sits on your own servers.
If your policy requires that nothing leaves your network at all, tell us at the first conversation. The non-AI parts of what we build — the ERP, the portal, the automation — can run entirely on your infrastructure, and for many businesses that is the sensible split.
Do you build the AI yourselves, or resell somebody else’s?
Neither, and the distinction matters. We do not train our own models — almost nobody outside a handful of large labs does, and any Indian software company claiming otherwise is worth questioning. We build on OpenAI’s API.
What is ours is everything around it: how your documents and data are prepared and fed in, how the output is validated before it reaches your system, what happens to the cases the model is unsure about, and how the whole thing connects to the software you actually run. That application layer is where an AI project succeeds or fails, and it is the part we build.
What is the sensible way to start with AI?
One narrow process, measured. Pick the task that is highest volume and most repetitive — usually document entry or first-line customer questions — and run it on your real material alongside the existing manual process for a few weeks. You get an accuracy figure from your own data rather than a claim from a vendor, and the cost of finding out is small.
What we would advise against is an open-ended “AI transformation” programme. Those are expensive, slow to show anything, and usually end with a pilot nobody deployed.
Tell us what isn’t working
A first conversation costs nothing and commits you to nothing. Bring the problem — the mess of spreadsheets, the report nobody can produce, the process that breaks every month-end. We will tell you honestly whether custom software is the answer, and roughly what it would take. Sometimes the answer is that you do not need us. We will say so.