LlamaIndex
AI data framework for RAG, retrieval, and semantic search.
LlamaIndex is an AI data framework for building RAG applications. It provides document loaders, indexing strategies, and retrieval pipelines that connect your data to LLMs for question-answering, search, and summarisation.
I use LlamaIndex to orchestrate the full retrieval pipeline - loading documents from various sources, chunking and indexing them, and retrieving the right context for each query. It supports multiple vector stores, embedding providers, and LLMs, so you can swap components as needed.
For Barnsley businesses building AI-powered Q&A or search over their own data, LlamaIndex handles the plumbing between your documents and the LLM. It manages the complexities of chunking, embedding, and retrieval so the AI gives accurate, grounded answers.
How I use LlamaIndex for Barnsley businesses
For search, it orchestrates indexing and retrieval for RAG applications.
Related integrations
Marqo
AI search API with built-in embedding and hybrid retrieval.
Pinecone
Vector DB for RAG and neural search over embeddings.
Qdrant
Vector database for similarity search and filtering.
Weaviate
Vector database with hybrid search and built-in embeddings.
Zilliz
Vector database for AI-powered semantic search at scale.
Want to discuss AI for your business?
I help businesses across South Yorkshire and beyond integrate AI into their workflows. Get in touch to talk through your specific situation.