Contract Analysis AI

Automated document review and risk assessment using Natural Language Processing.

Published May 15, 2024

1 min read

Technologies Used

Python

SpaCy

Hugging Face Transformers

Tesseract OCR

React

Interface highlighting risky clauses in a legal contract

Reviewing Contracts at the Speed of Light

Legal teams are buried under mountains of paperwork. Reviewing standard NDAs, MSAs, and vendor contracts consumes valuable hours that could be spent on high-level strategy. We built a Contract Analysis AI that reads documents, extracts key clauses, and flags potential risks (like non-standard liability caps) in seconds, acting as a tireless first-pass reviewer.

The Challenge

High volume of routine contracts creating a bottleneck.

Human error leading to missed risky clauses.

Inconsistency in contract terms across the organization.

High cost of outsourcing review to external counsel.

The Solution

Implemented OCR to digitize scanned PDFs and images.

Trained a Named Entity Recognition (NER) model to identify parties, dates, and amounts.

Fine-tuned a BERT model to classify clauses (e.g., Indemnity, Termination).

Built a comparison engine to check against the company's 'Playbook'.

Key Features

Clause Extraction

Automatically identify and tag 50+ common contract clauses.

Force Majeure
Confidentiality
Governing Law

Risk Flagging

Highlight terms that deviate from standard approved language.

Redlining suggestions
Risk severity score
Missing clause alerts

Search & Retrieval

Semantic search to find 'that one contract with the specific term'.

Natural language query
Metadata filtering
Version history

Technology Stack

Python

SpaCy

Hugging Face Transformers

Tesseract OCR

React

Project Timeline & Results

Week 1-4

Corpus Assembly

Annotated a dataset of 5,000 legal contracts.

Collected historical contracts. Worked with legal experts to label clauses and entities. Created a 'Gold Standard' dataset for training and validation.

Week 5-8

Model Training

Achieved 90% F1-score on clause classification.

Fine-tuned a pre-trained LegalBERT model. Implemented a rule-based layer for strict logic checks (e.g., 'Payment terms must be < 60 days'). Integrated Tesseract for OCR capabilities.

Week 9-12

User Interface

Reduced review time per NDA from 30 mins to 5 mins.

Built a split-screen interface: Document on left, AI insights on right. Added 'Accept/Reject' workflows for lawyers to validate AI suggestions. Deployed on a secure, private cloud.