Automated Invoice Processing

AI & Machine Learning • Intelligent OCR

Automated Invoice Processing

Extract data from invoices automatically using advanced OCR, organize your documents, and sync with your accounting software—all in one seamless workflow.

95%
Less Manual Entry
99%
Extraction Accuracy
<30s
Processing Time
1M+
Invoices Processed

The Challenge

Managing accounts payable was a bottleneck. The client processing thousands of invoices monthly relied on manual data entry, leading to frequent errors, lost documents, and delayed payments. They needed a solution to ingest invoices from various sources (email, scan, portal), extract key data fields (vendor, date, line items, total), and push it directly to their ERP system.

The Solution

We built an intelligent invoice processing pipeline called "Vellum Invoices". It leverages computer vision and LLMs to understand document layout and context, achieving near-perfect extraction accuracy even on non-standard invoice formats.

  • Multi-Modal Ingestion

    Automatically pulls invoices from email attachments, S3 buckets, and direct uploads, supporting PDF, JPG, and PNG formats.

  • Adaptive Extraction

    Unlike traditional template-based OCR, our LLM-powered engine adapts to new invoice layouts instantly without manual configuration.

  • ERP Sync

    Validated data is automatically formatted and pushed to NetSuite/QuickBooks, creating bills and attaching the original document image.

System Architecture

A serverless, event-driven pipeline optimized for scalability and security.

1. Ingestion & Pre-processing

Invoices arrive via webhook or upload. Images are optimized and converted to standard format using Python image libraries.

2. Vision & OCR

AWS Textract extracts raw text and table structures. Spatial data is preserved to help the LLM understand layout.

3. Semantic Parsing

OpenAI GPT-4 analyzes the raw text to identify vendors, dates, amounts, and line items, normalizing them to the target schema.

4. Validation & Storage

Extracted data runs through business logic rules (e.g., duplicate check, sum validation) before storage in PostgreSQL.

Tech Stack

AI & Vision
  • OpenAI GPT-4 Turbo
  • AWS Textract
  • OpenCV
Backend
  • Python (FastAPI)
  • Celery (Async Queues)
  • Redis
Data
  • PostgreSQL
  • AWS S3 (Document Storage)
Documentation & Quality
  • OpenAPI / Swagger
  • PyTest
  • Black / Pylint