Powabase functions as a Postgres backend specifically designed for AI applications. Each project receives its own dedicated database, authentication, storage, and compute resources. It integrates a Retrieval Augmented Generation (RAG) pipeline that automatically indexes documents upon upload, supporting various file types including PDFs, images, and office files. The platform also includes a built-in agent runtime, allowing for the creation of AI agents that can perform actions using tools over HTTP or MCP.
All these functionalities are accessible through a single REST API. Developers can connect their coding agents, such as Claude Code or Codex, to Powabase using an agent skill or MCP server to build backends from natural language prompts. The system supports advanced retrieval methods like vector, full-text, and hybrid search, along with state-of-the-art rerankers. Agents can be orchestrated into multi-step workflows using a visual builder, enabling complex automation and callable HTTP endpoints. Powabase emphasizes isolated project stacks for enhanced security and compliance, offering both a managed cloud service and a self-hostable open-source option.
Powabase targets developers, AI engineers, and teams building AI-powered applications, particularly those who require a robust backend with integrated RAG and agent capabilities.
Powabase offers a robust and integrated backend solution for AI application development, streamlining the deployment of RAG and agent functionalities. Its architecture provides project isolation and flexibility through both managed cloud and self-hosted options.
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