Search and retrieval
Semantic search over your documents, products, or knowledge base so users find what they need without exact keywords.
Traditional keyword search breaks when users don't know the right terms. AI-powered semantic search understands intent - so "how do I return a faulty item" finds your returns policy even if it never mentions "faulty".
I build AI search over documents, product catalogues, knowledge bases, and internal wikis. For Barnsley manufacturing firms, that might mean finding specs or procedures by describing the problem. For retailers, it's AI product discovery that understands "something like X but cheaper". For professional services, it's surfacing the right precedent or template. The tech (embeddings, vector search) is proven; the work is making AI search useful for your data and your users.
Example AI integrations
AI services and tools I've integrated for Barnsley businesses include:
Marqo
AI search API with built-in embedding and hybrid retrieval. For search, it powers semantic queries over documents and product catalogues.
Visit siteZilliz
Vector database for AI-powered semantic search at scale. For search, it stores embeddings and runs similarity queries at scale.
Visit sitePinecone
Vector DB for RAG and neural search over embeddings. For search, it indexes vectors for fast retrieval in RAG pipelines.
Visit siteWeaviate
Vector database with hybrid search and built-in embeddings. For search, it combines vector and keyword search for hybrid retrieval.
Visit siteQdrant
Vector database for similarity search and filtering. For search, it enables filtered similarity search over embeddings.
Visit siteLlamaIndex
AI data framework for RAG, retrieval, and semantic search. For search, it orchestrates indexing and retrieval for RAG applications.
Visit siteTypes of Barnsley businesses I work with on AI
- Manufacturing and engineering - Process documentation, quality checks, supplier comms, and internal knowledge bases. Often starting with one high-friction workflow.
- B2B SaaS and tech companies - Adding AI features to existing products, building internal tools, or prototyping new ideas with a clear path to production.
- Logistics and supply chain - Route optimisation, demand forecasting, inventory planning, and shipment tracking with AI.