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AI Document Processing and Invoice OCR Extraction
Extract, organise and process information from business documents using workflows that combine OCR, structured extraction, validation and AI where appropriate. We turn invoices, contracts, site reports, forms and other business documents, including scanned and handwritten ones, into structured data and push it into your ERP, CRM or accounting system, including Tally.
What We Build
Most businesses still re-type information from documents into their software. These are the document workflows we automate most often.
Invoice and purchase document processing
Supplier invoices and purchase documents read automatically: invoice number, supplier name, line items, totals and tax details captured as structured data.
Contract information extraction
Key details such as parties, dates, amounts and terms pulled from contracts and agreements into a searchable record.
Site reports and forms
Site reports, inspection sheets, application forms and other business documents converted from paper or PDF into data your team can report on.
Scanned and handwritten documents
OCR for scanned copies, phone photos and handwritten documents, with results checked against validation rules before they are used.
Document classification and summarisation
Incoming documents sorted by type and summarised, so each one reaches the right person or workflow.
Export to ERP, CRM and Tally
Validated data pushed into your ERP, CRM or accounting software, including Tally, instead of being typed in again. See Custom Software Development for the systems it feeds.
Extraction accuracy depends on document quality, formats and validation requirements. Uncertain results can be flagged for human review.
How It Works
Every document goes through the same five steps, whichever system it ends up in.
Typical document workflow
- Capture. Documents arrive by upload, email or scan.
- OCR. Text is read from scanned pages, photos, PDFs and handwriting.
- Extract. A language model identifies the fields you need, such as invoice number, supplier name, line items and totals, and tax details.
- Validate. Rules check totals, formats and duplicates; anything uncertain is flagged for a person to review.
- Export. Approved data is pushed into your ERP, CRM or accounting system, including Tally.
Architecture
A FastAPI service in Python runs the OCR and calls an OpenAI GPT-class model through its API to extract and structure the fields. Results are stored in MySQL, and a Laravel review screen shows each document beside its extracted data so your team can approve, correct or reject flagged items before export. It runs on your VPS or cloud account behind Cloudflare.
Why OCR alone is not enough
OCR turns an image into text, but it does not know which number is the invoice total and which is a phone number. The language model reads that text the way a person would, finds the fields you care about and returns them in a fixed structure, while validation rules catch what does not add up.
How we keep your data safe
Your data stays in your own database. For each request, the system sends the model only the records or passages that request needs, never your whole database, and access follows your user roles. We do not use your data to train AI models, credentials and API keys stay on the server, and we review the data-handling terms of any AI provider we use.
How a Document Automation Project Runs With Us
Six stages, starting with your real documents rather than samples.
1. Collect sample documents
We gather a representative set of your documents, including the messy ones: poor scans, handwriting and unusual layouts.
2. Define fields and rules
We agree which fields to extract from each document type and the validation rules that decide what needs review.
3. Build the pipeline
The OCR and extraction service is built and tested on your samples, with results you can check.
4. Review screen
Your team gets a screen to approve, correct or reject flagged documents before anything is exported.
5. Connect your systems
Approved data is connected to your ERP, CRM or accounting software, including Tally.
6. Monitor and improve
We track exceptions after launch and refine rules as new layouts and suppliers appear.
What Drives the Cost of Document Processing
We quote after reviewing a sample of your documents. These are the things that move the number.
- Document types and layouts. One invoice format from a few suppliers is simpler than many document types in dozens of layouts.
- Document quality. Clean PDFs are quicker to handle than poor scans, phone photos or handwriting.
- Fields and validation. The more fields you need and the stricter the checks, the more design and testing work.
- Volume. Processing and model usage charges grow with the number of pages each month.
- Destination systems. Each ERP, CRM or accounting integration, such as Tally, needs its own mapping and testing.
Send us a handful of your real documents and we will tell you what can be automated and what should stay with a person.
Related Work
Document processing pays off when the data lands in a system your team already uses. These are systems we built that hold exactly that kind of data.
Keystone QS HRMS & ERP
Attendance, payroll, projects and CRM for a quantity-surveying firm, in one system.
Pandit Constructions
A labour management system that replaced paper hajeri, wages and site expense records across every site.
Keystone Insight AI
A natural-language assistant over construction cost and quantity data, built on the Keystone QS systems.
Frequently Asked Questions
Still Typing Data from Documents?
Send us a few of the documents your team re-types every week. A 30-minute call is enough to say what can be automated, what needs review and which system the data should land in.