Real-time collaborative developer workspace featuring a workspace-wide RAG AI agent driven by Atlas Vector Search
This project is a Multimodal RAG system that extracts, processes, and indexes text, images, and tables from PDF documents to enable comprehensive document understanding. By leveraging specialized FAISS indexes and GPT-4V vision capabilities, it fetches relevant context across all modalities to generate accurate, cited answers to complex user querie
This project is a Multimodal RAG system that extracts, processes, and indexes text, images, and tables from PDF documents to enable comprehensive document understanding.
Governed patent warehouse and retrieval platform with SQL Server, dbt, BM25/semantic search, trace evidence, and review workflows.
Diagnostic engine for RAG retrieval failures. Component-level analysis, root cause detection, optimization recommendations. Fix what's broken, not just metrics.
Agentic data engineering with RAG (ChromaDB, FAISS), Databricks streaming (DLT, Autoloader, COPY INTO), medallion layers, caching, and Genie.
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