AI-Powered Precision in Critical Data Extraction

The client

Our client is a Fortune 500 company and a leading multinational conglomerate with a diverse portfolio of businesses that transform industries and improve lives. Our client operates in four key areas with a strong presence: aerospace, performance materials and technologies (PMT), building automation, and safety and productivity solutions (SPS). Given the complexity of their operations, the client depends on robust systems, including SAP, to manage customer service workflows and ensure seamless business processes.

Market trends in the aerospace industry

The aerospace and industrial sectors are swiftly advancing, propelled by industrial automation system, digital transformation, and increasing customer demands for speed and personalization. Companies are under growing pressure to integrate advanced technologies such as AI and cloud computing to boost efficiency and improve customer experiences, while regulatory requirements further drive the need for innovation and digital transformation in the aerospace industry.

For many modern aerospace firms, these trends expose operational bottlenecks in their customer service processes, including manual email handling, slow data retrieval from SAP systems, and incorrect classification of customer inquiries. Addressing these inefficiencies is crucial for enhancing service efficiency, meeting customer expectations, and staying competitive in the market.

Challenges

The client’s revenue recognition teams relied heavily on the extraction of critical data elements (CDEs) from processed sales and procurement contracts to assess termination/cancellation risks, ensure accurate revenue recognition, and reduce administrative overhead. However, this process posed several challenges:

Unstructured data format

• Contracts were stored in inconsistent and unstructured formats, making manual extraction time-consuming and error prone.

Lack of standardization

• Variations in contract templates and layouts hindered efficient data processing.

Language complexity

• Contracts often included intricate legal and technical language, adding to the difficulty of identifying and extracting key data points.

These issues resulted in a labor-intensive process that consumed significant time and resources, delaying decision-making and increasing operational costs.

LTIMindtree’s solution

To address these challenges, LTIMindtree partnered with the client to deploy an innovative, AI-driven solution leveraging Azure Open AI technology enabling a digital transformation in their aerospace business. The solution was designed to automate the extraction of CDEs, transforming a manual, cumbersome process into a seamless, efficient workflow. Key components of the solution included: 

• Automated data pipeline: A robotic process automation (RPA) pipeline was developed to extract and process contracts directly from Leap, the client’s contract lifecycle management (CLM) application, on a regular schedule. 
• CDE extraction for 47 data elements: The system was configured to process 47 specific questions (data elements) relevant to the client’s IA SBGs sales business groups (SBGs) contracts. 
• AI validation process: A CDE review mechanism was established to validate the AI-extracted results, ensuring accuracy and reliability. 
• User-friendly output: The solution enabled users to download extracted CDEs in Excel format, facilitating easy integration into downstream workflows.
• Prompt engineering: Advanced prompt engineering techniques were implemented to enhance the precision of AI-driven extraction tasks, tailoring the system to the client’s unique contract language and structure.

Tech stack

• Azure Open AI
• Robotic process automation (RPA)
• Excel
• Contract lifecycle management (CLM) application
• Critical data element (CDE) extraction and review mechanism
• Prompt engineering

Business Benefits

The deployment of LTIMindtree’s Azure Open AI-based solution delivered transformative outcomes for the client: 

• Automation of CDE extraction: The manual effort of extracting critical data from contracts was fully automated, eliminating repetitive tasks and manual effort. 
• Significant cost savings: The client achieved annual savings of $264,000 by reducing labor costs and improving efficiency. 
• Operational efficiency: A 100-hour reduction in monthly execution time , enabling faster decision-making and freeing up resources for higher-value activities. 

Scalability, agility and accuracy: The shift from a labor-intensive process to an automated, scalable workflow enhanced overall operational agility and accuracy.

Conclusion

By leveraging the latest Azure Open AI technology and LTIMindtree’s aerospace digital transformation expertise, the multinational conglomerate successfully overcame its contract data extraction challenges. The solution not only delivered measurable financial and operational benefits but also positioned the client to scale its revenue recognition processes effectively. This case study illustrates how AI-driven innovation can address complex business problems, driving efficiency and value in a competitive global market.

Testimonial

“Our AI-powered approach has unlocked new levels of efficiency for our client, showcasing the transformative potential of automation. It’s a proud milestone in delivering impactful solutions.”

Naushad Khambhawala – Vice President Manufacturing – Americas, LTIMindtree

Looking for an AI-powered precision in critical data extraction for your organization?

Reach out to us at mfg.communications@ltm.com