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Aug 31, 2023
2 min read

OAI Search

Search engine utilizing RAG framework, powered by Azure Cognitive Search and OpenAI for streamlined access to internal business documents

As an AI Engineer, I spearheaded the development of the backend infrastructure for the OAI Search project. This involved integrating OpenAI technologies, managing data processing and indexing, and conducting iterative performance optimizations. My primary objective was to incorporate feedback rapidly and set clear guidelines for MVP development, all within a stringent two-month deadline (in compliance with NDA).

Technologies Used

  • Programming Languages: Python
  • AI & Machine Learning: OpenAI, Azure Cognitive Services
  • Database Management: SQL, NoSQL
  • Other Tools: MS Office

Core Outcomes

  1. Improved Query Response Time: Achieved a dramatic reduction in the average query response time, from 12.5 seconds to 5.7 seconds, marking a 46% decrease.
  2. Increased Query Volume: For a subset of key users, there was an +85% increase in the number of queries processed monthly over a 6-month span.

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