Automated Document Review with AI for Efficient Contract Analysis

Automated Document Review and Contract Analysis

1. Document Submission

1.1 Client Upload

Clients upload legal documents and contracts through a secure portal.

1.2 Initial Verification

AI tools verify the authenticity and completeness of the submitted documents.

2. Pre-Processing of Documents

2.1 Text Extraction

Utilize Optical Character Recognition (OCR) tools such as Adobe Acrobat Pro or ABBYY FineReader to convert scanned documents into editable text.

2.2 Data Structuring

AI algorithms structure the extracted data into predefined categories for easier analysis.

3. Automated Review Process

3.1 Contract Analysis

Implement AI-driven contract analysis tools such as Kira Systems or Luminance to identify key clauses, obligations, and risks.

3.2 Compliance Checking

Use AI tools like LawGeex to ensure compliance with relevant regulations and company policies.

4. Risk Assessment

4.1 Risk Identification

Leverage machine learning models to assess potential risks associated with contract terms and conditions.

4.2 Risk Reporting

Generate detailed risk reports highlighting areas of concern using AI analytics platforms such as Everlaw.

5. Review and Approval Workflow

5.1 Human Review

Legal professionals review AI-generated reports and recommendations for accuracy and relevance.

5.2 Approval Process

Facilitate a streamlined approval process using project management tools like Asana or Trello to track the status of document revisions.

6. Finalization and Archiving

6.1 Document Finalization

Finalize contracts and documents based on human review feedback.

6.2 Secure Archiving

Utilize document management systems such as iManage or NetDocuments for secure storage and easy retrieval of finalized documents.

7. Continuous Improvement

7.1 Feedback Loop

Collect user feedback on the AI tools and workflow efficiency to identify areas for improvement.

7.2 AI Model Training

Continuously train AI models with new data to enhance accuracy and performance in future document reviews.