Client Background
Applied Intuition, a global leader in autonomous vehicle simulation technology, faced growing operational challenges with its high volume of Non-Disclosure Agreements (NDAs). Managing, extracting, and validating key terms from diverse NDA formats demanded significant manual effort, often leading to inefficiencies and compliance risks.
To resolve these challenges, Applied Intuition partnered with NextGen Coding Company to build a fully automated, AI-powered NDA processing system capable of scaling with organizational growth while ensuring accuracy, speed, and data compliance across global operations.
The Problem
Applied Intuition’s legal and administrative teams were overwhelmed by the time-intensive task of manually reviewing NDAs to extract critical fields such as:
Confidentiality and termination dates
Agreement types (Mutual, One-Way, Multi-Party)
Trade secret clauses and deletion rights
Strict marking requirements and NDA purposes
These manual workflows were prone to human error, lacked scalability, and risked non-compliance with regulations such as GDPR and CCPA. Applied Intuition required a secure, automated, and intelligent system to standardize NDA processing, improve data reliability, and reduce the administrative burden on its teams.
Our Solution
NextGen designed and deployed a comprehensive AI-driven automation framework using Nanonets, Python, and AWS-integrated architecture to extract, validate, and export structured NDA data securely.
Custom AI Model Development with Nanonets
Trained a custom Nanonets model on 20 NDA samples annotated with key metadata, including confidentiality terms, termination periods, and purpose clauses.
Leveraged iterative refinement by manually reviewing model predictions to boost accuracy and adapt to variable document layouts.
Configured the model to extract seven key fields:
Confidentiality Term Dates
Termination Dates
NDA Type
Deletion Rights
Trade Secret Protection
Strict Marking Requirements
NDA Purpose
Normalized extracted data formats (e.g., converting all date fields to DD-MM-YY) and validated Boolean fields for consistency.
Automated Workflow and Data Processing
Built an end-to-end data pipeline where NDAs could be uploaded via the Nanonets UI or programmatically through the Nanonets API.
Integrated Python-based post-processing scripts to handle exceptions such as missing termination dates or derived confidentiality terms.
Created a CSV export layer with field mapping and metadata tracking, ensuring seamless ingestion into Applied Intuition’s internal systems.
Workflow Integration and Scalability
Connected automated exports to Applied Intuition’s internal workflow tools through secure API endpoints.
Designed the pipeline for horizontal scalability, capable of handling thousands of NDAs without manual intervention.
Used AWS S3 for secure file storage and retrieval, ensuring fast access to processed results.
Compliance and Security Framework
Implemented AES-256 encryption for all data in transit and at rest.
Deployed role-based access control (RBAC) to limit sensitive data visibility to authorized personnel only.
Ensured full compliance with GDPR and CCPA, including anonymization protocols and audit-ready data trails.
Iterative Testing and Collaboration
Conducted multi-phase validation cycles with Applied Intuition’s legal team to refine extraction rules and improve precision across varied NDA templates.
Used insights from Nanonets’ best practices to optimize model confidence thresholds and fine-tune document parsing logic.
Implemented a regression testing suite to ensure consistent performance as new document variations were introduced.
Results
The automated NDA processing system transformed Applied Intuition’s document workflows, delivering measurable operational gains:
60% reduction in processing time, enabling near-instant extraction and validation of critical NDA data.
95% accuracy rate achieved through iterative training, reducing legal risk and manual review cycles.
Full compliance with GDPR and CCPA, reinforced by encryption and access control safeguards.
Seamless workflow integration via API, minimizing disruption to existing legal operations.
Scalable infrastructure capable of handling increasing document volumes with zero degradation in performance.
Enhanced user satisfaction, with Applied Intuition’s teams praising the system’s reliability, ease of use, and time-saving benefits.
By leveraging AI-driven document processing and automation, NextGen Coding Company delivered a solution that not only improved productivity but also strengthened compliance and data integrity.
Why It Matters
This project demonstrates how AI automation in legal operations can radically enhance accuracy, security, and efficiency. Applied Intuition’s implementation serves as a model for modern enterprises seeking to automate repetitive document workflows while ensuring regulatory compliance and scalability.
NextGen’s approach highlights the power of AI platforms like Nanonets, Python-based automation, and cloud integration in building secure, future-ready business systems.
Call to Action
NextGen designs AI-driven document automation systems that eliminate manual bottlenecks and enhance compliance accuracy. If your organization manages high document volumes, we can help you implement scalable, secure automation tailored to your workflows.
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