RAG with ReACT response synthesis. Async Deployment and Chainlit frontend
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Developed a sophisticated Retrieval-Augmented Generation (RAG) system that combines semantic search, lexical search, and web search capabilities with conversational memory for intelligent research assistance.
The system was built modularly and in a declarative paradigm. It ingests data from internet searches and encodes it with an optimized qdrant database very granularly for fine-grained retrieval
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An intelligent system that automates the complete RFP workflow - from natural language creation to AI-powered proposal evaluation. Features automatic email monitoring, multi-format document extraction (PDF, Word, Excel, Images), and intelligent vendor comparison.
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Sophisticated Retrieval-Augmented Generation (RAG) system that combines semantic search, lexical search, and metadata filtering to determine the characteristics of the profiles desired and return the most relevant resumes to the end user.
The system ingests a knowledge base constituted of resumes and encodes them into an optimized qdrant database after adding relevant metadata expected to be helpful during retrieval.
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