Pathway’s LLM App repository provides ready-to-deploy templates for building AI applications over live, continuously changing data. The templates cover retrieval-augmented generation, document indexing, enterprise search, multimodal RAG, and related pipelines that can stay synchronized with sources such as local files, Google Drive, SharePoint, S3, Kafka, PostgreSQL, and real-time APIs.

Unlike static RAG examples that require periodic re-indexing, Pathway focuses on live data processing so additions, updates, and deletions can propagate into search and AI results automatically. The templates include built-in indexing for vector, hybrid, and full-text search and can be deployed on cloud platforms or on premises. The repository is particularly useful for developers who want a production-oriented starting point for RAG systems that must remain current as enterprise data changes.