Powabase

Powabase focuses on giving teams a single backend for AI applications, combining Postgres, retrieval augmented generation (RAG), agents, and visual workflows in one stack. It targets developers building AI products who want managed Postgres with vectors, high quality retrieval pipelines, and an agent runtime without stitching together half a dozen separate services or building infrastructure from scratch.

What is Powabase? Powabase focuses on giving teams a single backend for AI applications, combining Postgres, retrieval augmented generation (RAG), agents, and visual workflows in one stack. It targets developers building AI products who want managed Postgres with vectors, high quality retrieval pipelines, and an agent runtime without stitching together half a dozen separate services or building infrastructure from scratch. Key Features: Unified Postgres + vector backend: Managed Postgres with row level security, pgvector for embeddings, built in auth, object storage, and realtime. Access comes via PostgREST for REST or GraphQL style queries, or through a direct database connection. Production grade RAG pipeline: Handles PDFs, images, Office files, and URLs, then automatically extracts, chunks, embeds, and indexes content. Multiple indexing strategies and hybrid, vector, and BM25 search are combined with modern rerankers, with benchmarked OCR and retrieval accuracy. Agent runtime with tools and sessions: Supports ReAct style agents across multiple LLMs, tools, and knowledge bases. Streaming over SSE exposes token deltas, retrieval events, tool calls, and citations, with session objects keeping multi turn state.