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Solutions/RAG Pipelines
Core AI & Agentic Systems

RAG & Knowledge Pipelines

Connect LLMs to your proprietary data with production-grade retrieval-augmented generation pipelines that deliver accurate, cited, and trustworthy answers.

Practice Area

Data AI

Delivery

8 wk avg. to production

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The problem

Generic chatbots hallucinate, drift from facts, and fail to access your internal knowledge base, making them untrustworthy for enterprise use where accuracy is non-negotiable.

Our approach

We implement enterprise RAG stacks with multi-format document ingestion, hybrid vector + BM25 retrieval, semantic re-ranking, query decomposition, and grounded answer generation.

How we deliver it.

Off-the-shelf LLMs don't know your business. We build end-to-end RAG systems that ingest your documents, contracts, manuals, and databases, chunk, embed, and index them, then serve accurate, citation-grounded answers at scale.

What's included

Every deliverable, defined.

01Multi-format ingestion: PDF, DOCX, HTML, web, databases
02Intelligent chunking and document hierarchy preservation
03Hybrid vector + BM25 / full-text retrieval
04Semantic re-ranking (Cohere Rerank, cross-encoders)
05Pinecone, Weaviate, Qdrant, pgvector deployment
06Query rewriting and HyDE for recall improvement
07Citation-grounded answer generation
08Continuous accuracy evaluation & drift monitoring

Related in this pillar

Multi-Agent AI Systems

Multi-Agent AI

LLM Fine-Tuning & Deployment

LLM Deployment

Computer Vision Systems

Computer Vision

Ready to build RAG Pipelines?

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