Case Study

AI-Powered Natural Language Cloud Infrastructure Deployment Platform Achieving 85% Accuracy in AWS Provisioning Tasks

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Industry 

Healthcare & Pharmaceuticals

Expertise 

Amazon CloudWatch, Amazon DynamoDB, AWS IAM, Amazon Bedrock

Offerings/solutions 

An AI-powered automation solution for cost sheet processing and analysis.

About the Client

The client is a top-tier, vertically integrated company focused on developing, manufacturing, and marketing pharmaceutical formulations worldwide, addressing unmet medical and societal needs. Operating under the Accord Healthcare umbrella, it spans over 85 countries with a strong presence in North America, Europe, Latin America, Asia-Pacific, CIS, and MENA regions, driven by organic growth and strategic acquisitions.

Highlights

80%

Accuracy in Deployment tasks

Natural Language Automation

Natural language commands

Enterprise-Grade Integration

Secure and Scalable Deployments

The Challenge

The client faces major challenges in efficiently managing and analyzing the approximately 1,500 cost sheets received monthly from various chemical vendors. The current manual processes for extracting, aggregating, comparing, and visualizing data from inconsistently formatted Excel sheets are labor-intensive, prone to errors, and cause significant delays in decision-making. This lack of automation limits their ability to quickly gain vendor-wise cost insights and make timely, data-driven vendor choices.

Solutions

• Amazon S3 was deployed to securely store incoming cost sheets using pre-signed URLs. Files automatically triggered AWS Lambda functions for processing.
• AWS Lambda served as the serverless compute engine for data extraction and query processing, leveraging Amazon Bedrock’s models to extract structured data from Excel sheets and generate SQL queries.
• Amazon RDS (Aurora PostgreSQL) functioned as the core component for structured data storage. Extracted data was stored in properly formatted database tables with vector embeddings for semantic similarity searches across vendor data.
• Amazon Bedrock provided AI capabilities through Anthropic Claude v3 Sonnet for SQL query generation & data extraction, Claude v3 Haiku for summarization, and Titan embedding models for vector representations.
• Amazon API Gateway exposed REST endpoints for query processing, forwarding user queries to AWS Lambda functions with authentication and rate limiting.

The Results

AI-powered platform that simplifies AWS infrastructure deployment through natural language commands, achieving 85% accuracy while accelerating provisioning with secure, scalable, and accessible chat-based automation.

Download the Case Study

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