Project-isolated backend stack
Each project gets its own Postgres database with RLS, plus auth, object storage, and realtime services exposed through PostgREST, a REST/GraphQL-style API, or a direct database connection.
Powabase
Powabase is a backend platform for AI apps that combines per-project Postgres, auth, storage, realtime, retrieval, agents, and workflows. It supports managed cloud and self-hosted deployment, plus bring-your-own LLM keys.
Overview
Powabase is an all-in-one backend platform for AI applications. It combines project-isolated Postgres with auth, storage, realtime, retrieval, agent runtime, and visual workflows so teams can build AI-native products without stitching together separate infrastructure.
The site positions Powabase as a single backend for apps that need RAG and agents, not just a database. It supports uploading source content for indexing, running agent loops with tools and citations, and deploying workflows as HTTP endpoints, while also offering managed cloud and self-hosted deployment options.
Core capabilities
Built-in RAG pipeline
Powabase can ingest PDFs, images, office files, and URLs, then extract, chunk, embed, and index them for retrieval. The site says it includes OCR, BM25, pgvector, hybrid search, and reranking.
Agent runtime with logs and citations
Agents run ReAct orchestrations with multiple LLMs, knowledge bases, and tools. The runtime supports streaming over SSE with logged retrieval events, tool calls, token deltas, and citations.
Visual workflows and HTTP endpoints
Workflows can be built visually by connecting triggers, conditions, agents, HTTP calls, and code blocks. A natural-language copilot can also design the flow, and deployed workflows can become HTTP endpoints.
Flexible deployment and model setup
The platform supports managed cloud, self-hosted Docker or Kubernetes deployments, and bring-your-own LLM keys. It lists OpenAI, Anthropic, Google, and OpenRouter as supported key providers.
Common use cases
Build an AI app backend
Use Powabase when you want to launch an AI product on a single backend that covers database, auth, storage, retrieval, and runtime instead of assembling each layer separately.
Create a retrieval-backed knowledge base
Use the RAG pipeline to turn documents, images, office files, or URLs into searchable project knowledge with chunking, embeddings, OCR, hybrid search, and reranking.
Run tool-using agents
Use the agent runtime for workflows that need tool use, multi-step reasoning, streamed outputs, and citations, including custom tools over HTTP or MCP.
Deploy internal or customer-facing workflows
Use the visual workflow builder when you need to connect triggers, conditions, agents, HTTP calls, and code into an endpoint your app can call.
Operate in managed or private environments
Use the deployment options when you need managed hosting, self-hosting, or private infrastructure with your own LLM keys and stricter security posture.
Pros and Cons
Pros
- Combines backend services, retrieval, agents, and workflows in one platform.
- Supports project-level isolation for Postgres, Realtime, and Storage.
- Offers both managed cloud and self-hosted deployment paths.
- Includes built-in retrieval features such as OCR, BM25, pgvector, hybrid search, and reranking.
- Supports bring-your-own LLM keys and multiple deployment targets for teams with different security requirements.
Cons
- The source material is lighter on concrete integration coverage beyond the named LLM providers, coding agents, and HTTP or MCP tools.
- Pricing and platform limits are described at a high level, but some operational details such as exact indexing options, retrieval tuning, and product boundaries are only partially documented here.
FAQ
Does Powabase have a free tier or paid plans?
Yes. The pricing page includes a Free plan, and paid plans add monthly credits that can be spent on compute hours, per-call costs, MAU overages, and storage. The site also says unused credits roll over month to month.
What is Powabase used for?
The site presents Powabase as a backend for AI apps that combines per-project Postgres, auth, storage, realtime, a RAG pipeline, agent runtime, and drag-and-drop workflows.
Can Powabase be self-hosted?
Yes. The site says it supports managed cloud deployment, self-hosting with Docker or Kubernetes, and bringing your own LLM keys. The pricing page also mentions private hosting in a VPC or on-prem for Enterprise.
Which models or coding agents does Powabase support?
The site says Powabase works with Claude Code, Codex, and Cursor when used with its agent skill, and that it supports bring-your-own keys for OpenAI, Anthropic, Google, and OpenRouter.
How do workflows and agents connect to external tools?
The site says workflows can be deployed as HTTP endpoints, and agents can use built-in tools such as web search and code execution or custom tools over HTTP or MCP.
Quick Facts
- Category
- Developer Tool
- Primary focus
- AI app backend with RAG and agents
- Deployment
- Managed cloud, Docker, Kubernetes, VPC, or on-prem for Enterprise
- Model support
- Bring your own keys for OpenAI, Anthropic, Google, and OpenRouter
- Website
- powabase.ai
- Pricing
- Free plan plus paid tiers with credits and usage-based billing
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