Case Study

Achieved an Accuracy Rate of Over 90% in Data Processing and Analysis, Ensuring High Precision and Reliability

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Industry 

FMCG

Expertise 

AWS Lambda, Amazon Bedrock, Amazon API Gateway, AWS IAM, Amazon RDS

Offerings/solutions 

Streamlined processes, cut analysis time, and improved insights with automation and integrated data.

About the Client

The client is one of the country’s leading FMCG marketers, the clear market leader in the Indian paperboard and packaging industry, a globally acknowledged pioneer in farmer empowerment through its extensive agribusiness, and a pre-eminent hotel chain in India.

Highlights

10 Minutes

Reduced Data Analysis Time

Responsive Frontend

Enhanced User Experience

90%

Increased Efficiency and Accuracy

The Challenge

The client encountered significant challenges in their business operations due to manual management of Supply chain data, which resulted in response delays and Data analysis. To address these issues, they aimed to enhance their workflow by integrating a Natural Language Text-based Chatbot into their infrastructure, enabling prompt and relevant responses to inquiries and fetching the required details in tabular and graphical format.

Solutions

• Developed three chat interfaces: Summarization, Graphical, and Tabular.
• Pre-processed and cleaned supply chain datasets using validation, transformation, and normalization.
• Inserted pre-processed datasets into Amazon RDS MySQL with appropriate tables for efficient querying.
• Used AWS Lambda and Amazon Bedrock to convert user queries into SQL queries.
• Executed SQL queries on Amazon RDS MySQL and processed the retrieved data.
• Summarized responses with Amazon Bedrock and delivered them via Amazon API Gateway.
• Generated and delivered graphical representations using Chart.JS and Amazon API Gateway.
• Provided tabular responses via Amazon API Gateway.
• Stored raw queries and summarized responses in Amazon DynamoDB for caching and future use.

The Results

Streamlined data workflows for quicker retrieval, cut analysis time to 10 minutes, improved user experience with clear and engaging insights, and achieved over 90% accuracy.

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