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DipanshuTechBuilding Digital. Driving Growth.

Automation

Document AutomationThe Paperwork That Files Itself.

Document automation for the paperwork that consumes the team — the intake, the extraction, the validation, the generation, the routing, the storage, with the audit trail and the accuracy eval the compliance and ops teams need to trust the automation in production.

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

Overview

Document automation is OCR plus a workflow plus a model

Document automation is the work of removing the repetitive part of paperwork — the intake, the extraction, the validation, the generation, the routing, the storage. The tool is OCR (Tesseract, AWS Textract, Google Document AI) plus a workflow engine plus a model for the judgment calls. The OCR is the engine, the workflow is the product.

We build document automations with the OCR, the extraction, the validation, the generation, the routing and the audit trail as part of the architecture from sprint one. The output is an automation 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. We will say so on the call.

  • Workflow Engineering — The workflow, the OCR, the rules and the integration engineered, not improvised.
  • 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.

What we deliver

Everything included in our document automation

Document Intake

Email, upload, scan, API — the document intake, in the format the source system uses.

OCR & Extraction

OCR + extraction against the schema, with the accuracy eval the use case needs.

Validation & Rules

The validation rules, the business rules, the cross-checks the document needs.

Generation & Templates

Document generation, the templates, the variables, the rendering the use case needs.

Routing & Storage

The routing, the storage, the audit trail and the retention the document needs.

AI & Judgment

The AI for the judgment calls — categorise, score, decide — 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 workflow, the OCR, the rules and the eval suite.

  3. 03

    Develop

    We build the automation, the integration and the audit trail 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
  • Camunda

Storage

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

What you can expect

Manual Effort Removed
70-90%Manual Effort Removed
Average Processing Time
<30sAverage Processing Time
Extraction Accuracy Target
99%+Extraction Accuracy Target
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.

The validation rules are part of the architecture. The OCR extracts, the rules engine validates, the model handles the judgment calls, and the human-in-the-loop handles the exceptions. The validation is the most important part of the system, because that is where the errors usually happen.

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 automation 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.