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Amazon Bedrock, AWS Lambda, Amazon EC2
Optimized query performance, data retrieval, cost efficiency, security, and resource utilization with minimal errors.
The client is an innovative company focused on making knowledge accessible to researchers and academic institutions, providing sustainable solutions to empower individuals in education, research, and publication. With over 4 years of experience, 10+ awards, and a growing client base, they are dedicated to transforming the research journey.
Query Performance and Scalability
High Accuracy
Cost Optimization
The client faces challenges in efficiently retrieving relevant and accurate information from a large repository of research papers while ensuring scalability and cost-effectiveness. They need robust infrastructure to handle diverse datasets, preprocess data, and meet domain-specific requirements, with added complexity from dependency on timely support for data access, APIs, and domain knowledge. Managing cost, performance, accuracy, and supporting complex queries remains a critical challenge.
• Postman sends queries via Amazon API Gateway to Amazon EC2 and AWS Lambda for processing.
• Amazon EC2 handles query-only requests, while AWS Lambda processes query+PDF cases.
• Flask backend on Amazon EC2 interacts with a secure Aurora PostgreSQL database.
• AWS Lambda uses Bedrock Haiku to process PDFs and queries, generating summaries.
• Database stores metadata and session histories with pgAdmin for management.
Optimized query processing with under 60 seconds response time, 90%+ accuracy, 1,000 queries per second, and minimized AWS costs while ensuring security and high resource utilization efficiency.
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