Solution
Invoice & Document Automation
So your team checks the numbers instead of typing them.
Python · Node.js · OCR services (Google Vision, Azure or open source)
4-step process
- 4 clear stagesCollect real samples to Tune on live documents
- Python, Node.jsand 4 more in the stack
- 6 kinds of worklisted below
- Written estimatefixed price, before work starts
What this is
Somewhere in your office a person is reading a supplier invoice and typing the same date, amount and GST number into a screen. Multiply that by every bill, receipt and form that comes in each week. Document automation uses OCR and a set of parsing rules to read those fields for you and put them into your accounting software or database. A person then reviews what was read, and that review step matters, because no OCR is perfect on a blurry photograph of a crumpled bill.
Who this is for
- Accounts teams keying in purchase invoices and expense bills by hand
- Distributors and retailers who receive many supplier bills every week
- Businesses sorting scanned forms, challans or delivery notes into records
- Firms that want PDF reports and letters generated from data instead of assembled manually
What problem this solves
If two or more of these sound familiar, it is worth a conversation.
Typing the same fields all day
Supplier, date, GST number, line items and total are retyped from paper or PDF into a system, which is slow and error-prone.
Bills wait in a pile
Entries are batched at month end, so payables and input credit are out of date for weeks.
Errors found too late
A wrong digit entered today shows up at reconciliation, when finding it takes far longer than typing it did.
Documents built by hand
Quotes, letters and reports copied from old files into a template, with a wrong name left in somewhere.
What Nimbryx actually builds
Every one of these is built around how your team already works.
Upload and capture
Staff upload a photo or PDF, or forward the bill to a dedicated email address.
Field extraction
OCR plus rules tuned to your most common invoice layouts to pull supplier, date, invoice number, GST details and totals.
Review screen
The document sits beside the extracted fields. A person corrects anything that is wrong and approves.
Checks and flags
Total versus line items, duplicate invoice numbers and GST number format checks before anything is posted.
Push to your system
Approved data goes to Tally, your database or a spreadsheet in the format you already use.
Document generation
Invoices, quotes, letters and reports produced from templates and live data, as PDF or Word.
How this typically works
From the first conversation to a working system.
Step 1
Collect real samples
We ask for a few dozen of your actual documents, including the ugly ones, because accuracy depends on them.
Step 2
Test extraction accuracy
We measure how many fields are read correctly on your samples and tell you the number before building further.
Step 3
Build the review flow
Upload, extraction, review and posting, with checks that catch the errors that matter to you.
Step 4
Tune on live documents
Accuracy improves as we add rules for the layouts you receive most.
The stack we’d likely use
Mature, well-supported tools. The final choice depends on your project, and we explain it before we start.
- Python
- Node.js
- OCR services (Google Vision, Azure or open source)
- PDF generation
- Tally export
- PostgreSQL or MySQL
An honest note
When this isn't the right call
If you process a few invoices a week, typing them is cheaper than building anything. If most of your documents are handwritten or very poor scans, accuracy will be low and a person will still need to key much of it. Some accounting tools already include invoice capture, so check yours first. We do not promise a fixed accuracy before seeing your documents, and we keep a human review step in the flow for anything that affects your accounts.
Not sure which side of the line you’re on? Ask us and we’ll say so.
How accurate is OCR on Indian invoices?
It depends on the layout and the scan quality. Printed, typed invoices from regular suppliers read well. Photos of folded bills read badly. We test on your own samples first and tell you the real number rather than quote a generic one.
Does it replace the person doing data entry?
It changes the job from typing to checking. Most teams keep the person and the volume they can handle goes up. Whether that saves headcount is your call.
Can it post directly into Tally?
Usually we generate an import file or use Tally's XML interface, and the approved entries are loaded after review. We confirm the method for your version during scoping.
Where are the documents stored?
On infrastructure you choose, in India if you prefer. If we use a third-party OCR service, we tell you what leaves your server before you agree to it.
Ready to talk about your project?
Tell us what you're trying to build. We'll reply within one business day with honest thoughts, not a sales pitch.
- First conversation is free
- Written estimate before anything starts
- You own the code