Reducing Manual Search Efforts by 50% with AI-Driven Data Retrieval

Reducing Manual Search Efforts by 50% with AI-Driven Data Retrieval

Pharma major enhanced its drug commercial data search capabilities using Altysys’ GenAI-powered solutions


About the company

The fourth largest multi-national pharmaceutical manufacturer by revenue.

Business Need

Pharmaceutical companies rely on vast commercial datasets to drive market strategy, regulatory compliance, and competitive insights. However, accessing the right data quickly remains a challenge. Data science and analytics teams often struggle with retrieving relevant commercial data from complex datasets stored across multiple sources. The lack of an intuitive search mechanism leads to inefficiencies, increasing the time required to identify and utilize key datasets.

Our client had a similar issue with their dataset containing commercial data of medical drugs stored in a Snowflake database. To address this challenge, the client approached Altysys to develop an advanced AI-powered solution that could:

  • Streamline the data search and retrieval process
  • Enhance accessibility to their commercial drug dataset
  • Accelerate and improve data discovery accuracy
  • Enable deeper insights for business intelligence and analytics

Solution

Following a comprehensive needs assessment, the Altysys team crafted a solution roadmap and executed these key initiatives:

  • Built a metadata-driven search framework within the Snowflake environment to accurately identify relevant databases and tables, ensuring precise query targeting.
  • Deployed an SQL agent to automate data extraction, enabling users to retrieve specific data points efficiently through direct queries or predefined conditions.
  • Integrated Retrieval-Augmented Generation (RAG) to enhance search accuracy for unstructured data, allowing AI-generated responses to incorporate relevant information from a vector database.
  • Implemented cosine similarity search to improve query matching, ensuring that users receive the most relevant datasets based on their search intent.
  • Leveraged Azure OpenAI embeddings and stored them in ChromaDB, optimizing data indexing and retrieval for faster, more accurate insights.

Tech Stack

GPT-3.5 Turbo, Azure OpenAI Service, FastAPI, React

Business Impact

  • 50-60% reduction in manual effort for metadata creation and searching
  • Improved search accuracy and result quality
  • Accelerated data discovery
  • Improved analytics and insights with AI-powered cognitive search

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