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Pharmaceutical Manufacturing
Amazon Bedrock, AWS Lambda, Amazon S3, Amazon DynamoDB, Amazon Aurora, Amazon CloudWatch
Automated workflow, enhanced deployments, improved reliability, and reduced costs.
Established in 1977, the global, technology-driven pharmaceutical manufacturer is known for delivering high-quality and affordable medicines worldwide. With a strong presence across more than 85 countries, the organization specializes in formulations, biosimilars, and complex generics. It operates through a vertically integrated model, supported by advanced research and development capabilities and world-class manufacturing facilities. Its continued focus on innovation, quality, and healthcare excellence has positioned the organization as a leading player in the pharmaceutical industry.
Automated Cost Sheet Workflow
Deployments across Dev, Stage, and Prod
Improved CI/CD stability
A global pharmaceutical manufacturer struggled with managing approximately 700 monthly vendor cost sheets across 50+ different templates, creating inconsistent data structures. The manual workflow for extracting, aggregating, and comparing cost information was resource-intensive and error-prone. Lack of automation caused decision-making delays as teams couldn’t derive timely insights from varying spreadsheet structures. Manual processes hindered accuracy in cost comparisons and vendor evaluations, while absence of centralized, structured data generation further complicated vendor cost analysis.
• Built GenAI-driven extraction workflow using Amazon Bedrock and AWS Lambda to automate diverse cost-sheet processing.
• Designed a structured data pipeline using Amazon S3, Amazon DynamoDB, and Amazon Aurora PostgreSQL for data storage.
• Developed secure frontend on Amazon S3 + Amazon CloudFront with Amazon Cognito authentication for uploads and chatbot insights.
• Implemented Azure DevOps pipelines for automated builds and deployments of frontend and Lambda functions.
• Enabled reliable multi-environment releases using versioned artifacts and Lambda aliasing.
• Strengthened observability and security with Amazon CloudWatch, AWS CloudTrail, AWS IAM, AWS KMS encryption, and Amazon Bedrock Guardrails.
• Delivered comprehensive documentation and handover for independent operation and scalability.
Automated end-to-end cost sheet workflow for ~700 monthly uploads using Amazon Bedrock-powered analytics, enabled consistent multi-environment deployments with Azure DevOps, improved reliability with versioned artifacts and AWS Lambda automation, and reduced operational costs through automated Amazon EC2 pipeline management.
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