From search to AI: How retrieval evolved

Search has evolved from exact matching and Boolean queries to semantic search, embeddings and AI systems that can retrieve, reason and act.

In this webinar, Sam Agbede will take you on a practical journey through the history of search: from TF-IDF and BM25 to semantic search, RAG and agentic retrieval. You will see how each generation of search solved a different challenge and why these foundations still matter for modern AI applications.

This webinar will also show how Redis 8 and Redis Search support full text, vector and hybrid search for real-time applications and AI workflows. You’ll leave with a clear mental model of modern retrieval and practical ideas for applying it to search, RAG and AI projects.

• How exact matching and Boolean search shaped information retrieval
• How TF-IDF and BM25 rank results across large document collections
• How embeddings and semantic search find meaning beyond exact keywords
• How RAG uses retrieved context to support more grounded AI responses
• How agents combine search, memory, tools and verification to complete larger tasks
• How Redis 8 and Redis Search bring full-text, vector and hybrid search to real-time applications
• Examples of retrieval and verification in mathematical research and agentic AI systems