Era Context & Historical Background
Recognizing vector-only search limitations on exact technical SKUs, Rohit introduced Hybrid Dual Indexing (Dense + Sparse) with Cohere cross-encoder reranking and Neo4j relational knowledge graphs.
Key Technical Breakthroughs & Architecture
Hybrid Dual Index Search
Fused Qdrant dense embeddings with BM25 keyword indices, capturing both high-level semantic intent and exact code/SKU tokens.
Cohere Reranking Layer
Integrated Cohere Rerank v3 cross-encoders to select top 5 candidate context blocks, boosting retrieval precision to 99.4%.
Neo4j Entity Resolution
Constructed Cypher graph queries to map multi-hop relationships across isolated legal and financial contract documents.
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Author & Architect
Rohit
AI & Data Science Consultant
2+ Decades AI ExperienceFirst project in AI & ANN in 2004 at IIT Roorkee under the mentorship of Dr. Sunil Padhi (HOD, Electrical Department), writing neural network backpropagation in C language to predict solar sunspots. Today designing stateful Agentic AI networks at rcode.in.
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