Automated entity extraction from legal documents using AI

Business Need

Automated data extraction to reduce the manual effort required, the startup needs a system that can automatically extract critical data (e.g., ownership details, rental terms, legal clauses) from unstructured legal documents such as property deeds and rental agreements.

Challenge

Handling unstructured data from diverse sources. Achieving high accuracy despite noisy or low-quality document scans.

Solution

AI Named Entity Recognition (NER)

Pipeline By leveraging advanced Natural Language Processing (NLP) techniques, specifically Named Entity Recognition (NER), the startup implemented a robust AI pipeline capable of extracting 35 critical entities from unstructured documents with over 90% accuracy.

Results

• Processed thousands of documents with minimal human intervention.
• Provided a seamless experience for users while empowering staff with reliable data.