Powabase: Build AI Apps with Postgres, RAG, and Agents

Build AI apps with Postgres, RAG, and agents - Powabase | Product Hunt

Powabase

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Build AI apps with Postgres, RAG, and agents

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Build AI apps with Postgres, RAG, and agents

8 followers

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Databases and backend frameworks

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AI Infrastructure Tools

Powabase is a backend-as-a-service for AI-native applications, combining Postgres, RAG, agents, memory, workflows, and automation primitives in one platform. It helps agencies and in-house IT teams build new AI apps or add AI automation to existing products without stitching together fragmented infrastructure. Designed to work seamlessly with modern coding agents, Powabase helps teams ship faster while building more robust, token-efficient systems.

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Launch tags:Developer Tools•Artificial Intelligence•Database

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Hey Product Hunt 👋

I'm Hunter, co-founder of Powabase. We've been running an AI dev shop since ChatGPT first came out, and after many client projects we noticed the same pattern repeating itself. Nearly every AI-native app ends up needing the same stack: Postgres, a vector store, RAG pipelines, an agent runtime, memory, auth, and file storage.

Today you stitch that together from 6–8 tools, write a lot of glue code, and then watch your coding agent burn tokens navigating it. We've built ~100 production AI apps across regulated industries — finance, insurance, education, government — and the infra glue was always the slowest, most expensive part.

So we abstracted it into a unified backend. Powabase is the backend we wished we'd had — and now every new AI project we take on ships in a fraction of the time.

Powabase is that whole stack as one platform:

Postgres + pgvector + file storage, provisioned per project in one click

Standard Supabase features like auth and realtime

A context engineering layer with multiple RAG algorithms that hits 98.7% on FinanceBench

Supports OpenAI, Anthropic, Google, or open-source LLMs via OpenRouter

Multimodal embeddings, rerankers, OCR, web search, web scraping all included without separate third party API keys or integrations

ReAct multi-agent orchestration with prebuilt tools (web search, database r/w, sandboxed code execution, etc.) and support for custom tool integrations via API and MCP

N8n-like visual agent workflow builder for deterministic logic; built-in copilot can help you craft workflows using natural language

Full observability in agent reasoning, token usage, RAG context, tool calls, workflow executions, and system errors

Optimized for coding agents like Claude Code — clean primitives, predictable APIs, token-efficient by design

AI apps deserve their own backend abstraction, not a Frankenstein of generic infra + LLM wrappers. Supabase made Postgres easy to use; we want to do that for the full AI-native stack.

It's free to start, and our cookbook + example apps are open source on GitHub. We plan to open source a self-hosted version after early access period ends, likely around late June / July 2026.

I'll be in the comments all day with @tonyzhangcy , @xin_chen17 , and @michael_t_chang . Tear it apart — what's missing, what's confusing, what would make you actually try it. 🙏

Early access users get free lifetime benefits — try it at app.powabase.ai and tell us what you build 🚀

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7d ago

the 6-8 tools stitched together with glue code is painfully accurate. every AI project starts clean and ends up as a frankenstein of integrations within a month. unified backend makes sense if it actually reduces that sprawl

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2m ago