Revolutionizing NDA Management with AI-Driven Automation for Applied Intuition

NextGen Coding Company developed a comprehensive, AI-driven NDA management solution tailored to Applied Intuition’s unique needs. The system combined advanced automation, custom workflows, and robust data security measures to deliver exceptional performance and reliability.

Custom Model Creation with Nanonets

• Training the Model:
  The Nanonets AI platform was used to create a custom model specifically designed to process NDAs in diverse formats. A dataset of 20 sample NDAs was utilized for training. Each document was annotated to identify and label specific fields, such as confidentiality dates, termination periods, and NDA types. Once the model was trained, every prediction was manually reviewed, ensuring high accuracy by refining the model’s confidence scores. This iterative refinement process enabled the model to handle a broad range of scenarios, including non-standard document structures.

Key Field Extraction:
Seven essential fields were mapped for automated extraction:

• Confidentiality Term Dates: The system extracted specific dates tied to confidentiality obligations, ensuring accuracy in handling complex date logic.
• Termination Dates: The start and end dates of the agreement were identified and validated for consistency across sections of the document.
• NDA Type: The model categorized NDAs as Mutual, One-Way, or Multi-Party, adapting to various business requirements.
• Deletion Rights: Boolean values were extracted to indicate whether deletion rights were requested, ensuring compliance with organizational preferences.
• Trade Secret Protection: The system flagged perpetual trade secret obligations, ensuring such terms were correctly identified and reported.
• Strict Marking Requirements: The AI detected whether confidential information needed explicit labeling, ensuring compliance with marking protocols.
• NDA Purpose: The purpose was categorized as exploring a business relationship, collaborating on a project, or other custom-defined purposes.

Validation and Normalization:

• Extracted data underwent rigorous validation to ensure consistency and accuracy. For example, all dates were normalized into the DD-MM-YY format, and boolean values were checked for logical consistency across sections.

Automated Workflow Design

• Data Intake and Processing:
  NDAs were uploaded to the system manually via the Nanonets interface or programmatically using the Nanonets API. Upon upload, the AI model extracted the required fields and validated them against predefined rules. This process eliminated the need for manual input, significantly reducing processing time and error rates.
• Post-Processing Enhancements:
  Python-based scripts extended the system’s capabilities, handling advanced scenarios like missing termination dates or complex confidentiality terms. These scripts added flexibility by recalculating fields dynamically based on relationships between dates, such as deriving confidentiality dates from termination periods. Learn more about Python-based post-processing from Python’s official documentation.
• Exporting and Integration:
  Extracted data was organized into CSV files, which included all mapped fields and metadata, such as file names. These files were exported to Applied Intuition’s internal systems, enabling seamless integration with existing workflows. The Nanonets API facilitated automated uploads and downloads, creating an end-to-end automated process that was scalable and efficient.

Compliance and Security Measures

• Data Security:
  Sensitive information was encrypted both in transit and at rest, meeting industry standards for data protection under GDPR and CCPA. Role-based access controls ensured that only authorized personnel could access processed data, minimizing risks associated with unauthorized access.
• Scalable and Reliable Infrastructure:
  The trained model was designed to scale effortlessly, handling increasing volumes of NDAs with minimal manual intervention. This scalability allowed Applied Intuition to accommodate growing business needs without compromising accuracy or performance.

Iterative Testing and Collaboration

• Collaborative Refinements:
  Applied Intuition’s legal and technical teams worked closely with NextGen to refine the system, ensuring alignment with business objectives and compliance standards. Regular feedback sessions allowed for continuous improvement and customization of the workflows.
• Extensive Testing:
  The system underwent rigorous testing to address diverse NDA formats and edge cases. Special attention was given to scenarios involving missing or inconsistent data, ensuring the system could handle even the most complex documents with precision. The testing also benefited from insights shared on Nanonets’ blog about best practices for AI-driven document processing.

The AI-powered NDA management system delivered transformative results for Applied Intuition, providing significant benefits in efficiency, accuracy, and scalability:

• Improved Efficiency:
  Automation reduced NDA processing time by 60%, allowing Applied Intuition’s legal team to focus on strategic initiatives rather than manual data entry. Tasks that previously took hours could now be completed in minutes, freeing up valuable resources for other high-priority activities.
• Enhanced Accuracy:
  By leveraging Nanonets’ AI capabilities and Python-based refinements, the system achieved an accuracy rate of 95%. Critical fields, such as confidentiality dates and termination periods, were extracted with precision, minimizing errors that could lead to compliance issues or operational inefficiencies.
• Streamlined Workflows:
  Exported data integrated seamlessly into Applied Intuition’s internal systems through the Nanonets API. This automation not only improved the organization and accessibility of data but also ensured consistency across all business processes, reducing the need for redundant work.
• Compliance and Security:
  The system’s robust encryption protocols and validation rules ensured full compliance with regulatory frameworks, such as GDPR and CCPA. This enhanced the company’s reputation for data privacy and reduced legal risks associated with non-compliance.
• Scalability and Flexibility:
  The trained model and automated workflows were designed to scale with Applied Intuition’s needs, processing additional document types and higher volumes without significant adjustments. This adaptability ensured long-term value and operational resilience.
• Increased User Satisfaction:
  Simplified workflows and faster turnaround times significantly improved satisfaction among Applied Intuition’s legal and administrative teams. Post-implementation feedback highlighted the system’s ease of use and reliability, reinforcing its value as a critical business tool.

By implementing an AI-driven NDA management system, NextGen Coding Company transformed Applied Intuition’s document processing workflows, delivering a secure, scalable, and efficient solution that set a new standard for operational excellence and compliance. This project exemplifies the value of combining cutting-edge technology with tailored development expertise.