Document & OCR Automation

Automate document processing — invoices, forms, reports — using OCR and AI to extract structured data and trigger downstream workflows, replacing hours of manual data entry.

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Overview

What You Get

From invoice processing to compliance form extraction, I build OCR and document automation pipelines that handle the full lifecycle: ingestion, extraction, validation, and integration into your existing systems. Using Robocorp RPA, PaddleOCR, and LLM-based extraction for complex layouts.

Process

How I Work

  1. 1

    Sample Review

    Analyze 20–50 sample documents to identify extraction targets and edge cases.

  2. 2

    Extraction Pipeline

    Build OCR + LLM extraction for structured fields, tables, and handwritten text.

  3. 3

    Validation Rules

    Define validation logic: required fields, cross-field checks, confidence thresholds.

  4. 4

    Integration

    Route extracted data to your ERP, database, or downstream API via webhook or scheduled batch.

  5. 5

    Exception Handling

    Build a review queue for low-confidence extractions that require human verification.

Benefits

Why Choose This Service

  • Reduce document processing time by 80%+ vs manual entry
  • Eliminate human transcription errors for structured fields
  • Scales to thousands of documents per day without added headcount
  • Handles PDFs, scanned images, handwritten forms, and mixed layouts
  • Provides confidence scores so low-quality extractions get flagged for review

Deliverables

What You Receive

  • End-to-end document processing pipeline
  • Extraction schema and validation rules
  • REST API for document submission and status tracking
  • Human review queue for exception cases
  • Accuracy metrics report on your sample dataset

FAQ

Common Questions

What document types can be processed?

PDFs, scanned images, handwritten forms, and mixed layouts such as invoices, forms, and reports.

What do you need from us to start?

A set of sample documents. The first step reviews roughly 20 to 50 samples to define the fields to extract and the edge cases to handle.

What happens with documents the system is unsure about?

Each extraction carries a confidence score. Low-confidence results go to a human review queue instead of flowing straight into your systems.

Where does the extracted data go?

Into your ERP, database, or downstream API, either by webhook or by scheduled batch.

How will we know the accuracy?

You receive an accuracy metrics report measured on your own sample dataset.