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RAG Systems
Retrieval-Augmented Generation systems that ground AI responses in your proprietary knowledge base for accurate, contextual outputs.
RAG Systems
We implement production-grade RAG pipelines that connect large language models to your proprietary data sources.
Architecture
- Vector Databases: Pinecone, Weaviate, pgvector
- Embedding Models: OpenAI, Cohere, custom models
- Chunking Strategies: Semantic, fixed-size, recursive
- Retrieval Optimization: Hybrid search, re-ranking, query expansion