RAG/GraphRAG Systems

Enterprise Knowledge Retrieval & Reasoning

Overview

We build retrieval pipelines, vector search integration, and graph-structured context for relationship-aware reasoning. Our RAG/GraphRAG systems deliver higher factuality, deeper explanations (the "why"), reduced hallucination, and reusable knowledge assets.

These systems are ideal for knowledge-heavy products, customer support, and analytics assistants that need to ground their answers in your actual data and relationships.

Key Deliverables

Technical Excellence

Approach & Methodology

  • Knowledge Extraction: Parse documents, databases, APIs into structured knowledge
  • Vector Indexing: Embed and index content for semantic similarity search
  • Graph Construction: Build relationship graphs between entities and concepts
  • Context Retrieval: Combine vector search with graph traversal for rich context
  • Answer Generation: Use retrieved context to generate accurate, grounded responses

Technology Stack

  • Retrieval: FAISS, Pinecone, Weaviate, Qdrant for vector stores
  • Graph: Neo4j, NetworkX, graph embeddings
  • Processing: LangChain, LlamaIndex, sentence-transformers
  • Backend: FastAPI, async processing, streaming responses
  • Monitoring: Answer quality metrics, retrieval relevance scores

Measurable Impact

Expected Results

  • Higher factuality and reduced hallucination in AI responses
  • Deeper explanations with relationship-aware context
  • Reusable knowledge assets that grow with your data
  • Traceable answers with source citations

KPIs We Track

  • Answer accuracy rate
  • Retrieval relevance score
  • Context window utilization
  • Query latency (p50, p95, p99)
  • Knowledge base coverage

How We Work Together

Knowledge Audit → Pipeline Build → Integration → Optimization

  • Knowledge Audit (1 week): Assess data sources, identify key relationships
  • Pipeline Build (2-4 weeks): Implement retrieval, vector search, graph construction
  • Integration (2-3 weeks): Connect to applications, implement APIs
  • Optimization (ongoing): Tune retrieval, expand knowledge, improve accuracy

Ready to Get Started?

Let's discuss how RAG/GraphRAG Systems can transform your business