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DipanshuTechBuilding Digital. Driving Growth.

AI + Data

Document Intelligence & OCRThe Typed Answer From the Paper.

Document intelligence and OCR for the typed answer from the paper — the OCR, the extraction, the validation, the classification, the routing, the audit trail and the accuracy eval the compliance and ops teams need to trust in production.

10+Years Experience
100+Projects Delivered
50+Expert Developers
20+Industries Served

Overview

Document intelligence is OCR plus a model plus a workflow

Document intelligence is the work of turning a paper document into structured data — invoices, receipts, contracts, IDs, KYC, the typed documents the business runs on. The work is the OCR, the extraction, the validation, the classification, the routing, the audit trail. The OCR is the engine, the workflow is the product.

We build document intelligence systems with the OCR, the extraction, the validation, the classification, the routing, the audit trail and the eval suite as part of the architecture from sprint one. The output is a system the compliance and ops teams can trust in production, not a script that breaks on the second document.

This is the wrong engagement if the document volume does not justify the build, or if the documents are genuinely unstructured (handwritten, low quality). We will say so on the call.

  • Accuracy Eval — An accuracy eval that runs on every change, with the regressions caught early.
  • Audit Trail — Every step logged with the user, the inputs, the outputs and the timestamp.
  • Compliance-Ready — The retention, the access control and the audit trail the compliance review needs.
  • On Your Infra — On your infrastructure, with the deployment model the data posture requires.

What we deliver

Everything included in our document intelligence & ocr

Invoice & Receipt OCR

OCR + extraction for invoices, receipts, the documents the AP team handles.

KYC & ID OCR

OCR + extraction for KYC, IDs, the documents the onboarding team handles.

Contract Intelligence

Contract parsing, clause extraction, the metadata the legal team needs.

Medical Records

OCR on medical records, lab reports, the documents the clinical team handles.

Logistics Documents

Shipping labels, customs forms, ePODs, the documents the logistics team handles.

Custom Document AI

A custom model against the document type the business handles, with the eval suite.

Our process

A proven process for successful delivery

  1. 01

    Discover

    We audit the documents, the volume, the schema and the accuracy the use case needs.

  2. 02

    Plan & Design

    We design the OCR, the extraction, the validation and the eval suite.

  3. 03

    Develop

    We build the pipeline, the model and the eval suite in sprints.

  4. 04

    Deploy

    We ship to production with the eval, the audit trail and the runbook live.

  5. 05

    Optimize & Grow

    We read the accuracy, the eval and the team feedback, and ship the next iteration.

Technology

Built with a stack that stays maintainable

OCR

  • AWS Textract
  • Google Document AI
  • Azure Form Recognizer
  • Tesseract

AI Layer

  • OpenAI
  • Anthropic
  • Google Gemini
  • Custom models

Workflow

  • n8n
  • Temporal
  • Airflow
  • Custom

Storage

  • S3
  • Google Cloud Storage
  • Azure Blob
  • On-premise

What you can expect

Extraction Accuracy (Structured)
99%+Extraction Accuracy (Structured)
Accuracy (Semi-Structured)
90%+Accuracy (Semi-Structured)
Average Processing Time
<30sAverage Processing Time
Audit Trail on Every Step
100%Audit Trail on Every Step

FAQs

Questions we get asked

Something not covered here? Ask us directly.

Invoices, receipts, contracts, IDs, KYC documents, medical records, shipping documents, customs forms, the typed documents the business runs on. The accuracy is a function of the OCR, the extraction and the eval suite, and the eval is tuned against the document type.

It depends on the document, the schema and the quality. For a structured document (invoice, receipt), 99%+ is a reasonable target. For a semi-structured document (contract, KYC), 90–95% is typical. The accuracy is measured against a held-out test set, not a guess.

Handwritten documents are a separate challenge. We use a higher-quality OCR (Azure Read API, Google Vision) and a model trained on handwritten samples. The accuracy is lower (70–85%) and the human-in-the-loop is usually part of the architecture. We will say so on the call.

Yes, when the data posture requires it. The OCR, the workflow and the storage can all run on your infrastructure, with the audit trail and the encryption the compliance review needs. The architecture is deployment-agnostic, with the choice made in the discovery.

Ready to start your document intelligence & ocr project?Let’s scope it together.

Tell us the outcome you need. We’ll come back with an approach, a timeline and a written estimate.