ENTERPRISE RAG & KNOWLEDGE GRAPHS

Enterprise RAG & Hybrid Knowledge Graph Search

Sub-100ms multi-modal document search querying millions of corporate PDFs, contracts, and research papers with zero hallucinations.

Lead Architect: Rohit • Target Outcome: 99.4% Retrieval Precision

Service Overview & Business Impact

Standard vector search misses exact keyword SKUs and complex document relationships. Our Enterprise RAG service combines dense vector embeddings, sparse keyword matching, and Neo4j entity knowledge graphs with Cohere reranking.

QdrantPineconeCohere RerankLlamaIndexNeo4jBM25

4-Layer Engineering Architecture

Layer 1: Multi-Modal Ingestion & Chunking

Parses complex PDF layouts, tables, and images using Unstructured and layout-aware semantic chunking.

Layer 2: Hybrid Dual Indexing

Indexes document chunks into Qdrant dense vector collections alongside BM25 sparse keyword indices.

Layer 3: Cross-Encoder Reranking

Reranks top candidate passages using Cohere Rerank v3 to pass only the top 5 most relevant context blocks to the LLM.

Layer 4: Knowledge Graph Reasoning

Queries Neo4j entity graphs to resolve multi-hop relational dependencies across isolated documents.

Implementation Roadmap & Deliverables

Phase 1: Knowledge Base Audit & Schema Design
Analyze document formats, metadata structures, and entity-relationship models.
Phase 2: Hybrid Index Pipeline
Set up Qdrant vector store and BM25 sparse search indexing pipelines.
Phase 3: Reranker & Guardrail Tuning
Integrate Cohere rerankers and hallucination prevention verification layers.
Phase 4: Production Handoff & Monitoring
Deploy scalable RAG API endpoints with latency monitoring dashboards.

Ready to Deploy This AI Architecture?

Book a 1-on-1 technical scoping session directly with AI & Data Science Consultant Rohit.

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Consultant Profile

Rohit - AI Consultant

Rohit

AI & Data Science Consultant

2+ Decades AI Experience

Building neural networks since 2004 at IIT Roorkee (mentored by Dr. Sunil Padhi, HOD Electrical Dept) and Unix CDR automation scripts at Xalted Bengaluru in 2007 (mentored by Srinivas Sir). Specializing in Agentic AI, Enterprise RAG, and MLOps.

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