AI

AI Invoice
Company Extractor

Built a hybrid AI document-processing system combining OpenAI Vision and OCR to extract issuing company names from PDF invoices. The solution validates extracted data against Excel-based business rules and automatically updates records, eliminating manual verification and improving financial data accuracy

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AI Invoice Company Extractor
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Technologies Used

Built with cutting-edge technologies to ensure scalability, reliability, and performance

Open AI Open AI Vision API
Python Python
Excel Excel
OCR OCR

How It Works

A closer look at the automated workflow behind the results

1

PDF Invoice Ingestion

Incoming PDF invoices are picked up by the Python pipeline as they arrive, queued for automated data extraction.

2

Hybrid Vision + OCR Extraction

OpenAI Vision and OCR work together to read each invoice and extract the issuing company name with high accuracy.

3

Rule-Based Validation & Update

Extracted names are checked against Excel-based business rules, and matching records are updated automatically without manual review.

Results & Impact

Measurable outcomes that demonstrate the real-world value delivered to the client

Processed 10,000+ PDF invoices with automated company name extraction
Achieved 96% extraction accuracy using hybrid Vision + OCR validation
Reduced manual invoice verification time by 70% across finance operations
Automated rule-based validation against Excel datasets, ensuring 99% compliance with business standards

Business Impact

For finance teams processing large volumes of invoices, manually reading each PDF to identify the issuing company and reconcile it against business records is slow and vulnerable to human error. Combining vision-based AI with OCR to extract and validate that data automatically removes the bulk of that manual review, letting finance staff focus on exceptions rather than routine checks. That means invoices move through the pipeline faster, records stay more accurate, and the process holds up as invoice volume grows.

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