Overview
Powabase is a backend-as-a-service platform built for AI-native applications. Instead of stitching together a Postgres host, a vector database, a RAG pipeline, an agent framework, an auth provider, and object storage as separate services, Powabase ships them as one platform — Postgres with pgvector, document ingestion with OCR, retrieval-augmented generation, multi-agent orchestration, authentication, storage, realtime, and workflow automation behind a single project.
The positioning is "Supabase for the AI stack." A developer provisions a project and gets a Postgres database with row-level security, plus the retrieval and AI agent layers that AI apps actually need — without wiring Pinecone, LangChain, and a separate orchestration runtime into the same codebase. It supports OpenAI, Anthropic, Google, and OpenRouter as model providers on a bring-your-own-keys basis, with keys encrypted at rest per project.
Powabase targets agencies and in-house engineering teams building new AI apps or bolting AI automation onto existing products. Early customers shown on the site include MIT, Cegid, Ytel, and DAOU. The product is in early access, where the full feature set is free, and it's explicitly optimized for coding agents like Claude Code, Codex, and Cursor.
Key Features
- Postgres + pgvector in one project — Every project gets a Postgres database with row-level security, object storage, auth, and realtime, plus native pgvector for embeddings — the relational and vector layers live together rather than in two synced systems.
- RAG ingestion pipeline — Upload PDFs, images, office files, or URLs and Powabase extracts, chunks, embeds, and indexes them, with multiple indexing strategies and multiple retrieval modes (including reranking) rather than a single fixed pipeline.
- Multi-agent orchestration — Build agents that run ReAct loops over multiple LLMs and knowledge bases, and compose them into multi-agent orchestrations — the AI workflow layer is part of the backend, not an external service.
- Visual workflow builder with NL copilot — A drag-and-drop builder with a natural-language copilot for designing flows, plus an API path for the same workflows so teams aren't locked into the visual editor.
- MCP support and coding-agent optimization — Native Model Context Protocol support plus optimization for Claude Code, Codex, and Cursor means a coding agent can scaffold and operate a Powabase backend directly.
- Built-in observability — Dashboards for token usage and agent reasoning are built in, so teams can see what an agent did and what it cost without bolting on a separate tracing tool.
How to Get Started
- Sign up at powabase.ai — Early access is free with the full feature set according to the pricing page (currently listed as running until June 30, 2026).
- Provision a project — Each project comes with Postgres + pgvector, auth, storage, and realtime out of the box.
- Bring your LLM access — Add OpenAI, Anthropic, Google, or OpenRouter keys, or use Powabase-provided LLM access/credits where available; stored keys are encrypted at rest per project.
- Ingest knowledge — Upload PDFs, images, office files, or URLs; Powabase extracts, chunks, embeds, and indexes them for retrieval.
- Build agents and workflows — Use the visual builder (with NL copilot) or the API to compose ReAct agents and multi-agent orchestrations. Call agents and workflows through Powabase REST/SSE APIs, use PostgREST for database tables, and connect MCP servers as agent tools.
- Deploy — Stay on Powabase Cloud (managed). For Enterprise Private Hosting/commercial deployments, Powabase lists single-tenant AWS/GCP/Azure/on-prem options with Helm for Kubernetes or Compose for a single host.
How It Compares
- vs. Supabase — Supabase is the clear reference point: both give Postgres-plus-auth-plus-storage as a managed backend. Powabase's wedge is the AI layer — pgvector, RAG ingestion, agents, and orchestration are first-class rather than something the developer assembles on top of Supabase with external services.
- vs. Firebase — Firebase is document-database-first and Google-ecosystem-bound. Powabase is Postgres-first (relational + SQL + RLS) with the AI retrieval/agent layer added, which fits teams that want SQL and vector search in the same database.
- vs. LangChain / LlamaIndex + a vector DB — Those are libraries the team wires into its own backend. Powabase is the managed backend itself, trading some flexibility for not having to operate Pinecone + an orchestration runtime + a Postgres host separately.
- vs. Convex / Vercel AI stack — Those lean serverless-first with their own data models. Powabase stays on standard Postgres, so existing SQL skills and tooling transfer, and self-hosting is a first-class option.
The honest read: Powabase is best for teams that want the Supabase developer experience but with the AI retrieval and agent layers built in. It's a worse fit for teams already deep in a Supabase + bespoke-RAG stack that works.
Pricing & Plans
Powabase is free during early access, which the pricing page currently states runs until June 30, 2026. After early access, published Self Serve/Scale pricing is consumption-based per action; no fixed monthly self-serve tier is listed.
| Plan | Price | What's Included |
|---|---|---|
| Free (Early Access, until Jun 30 2026) | $0 | All platform features: per-project Postgres + pgvector, auth, storage, realtime, document ingestion with OCR, multiple indexing strategies, multiple retrieval modes, ReAct agents, multi-agent orchestrations, visual + API workflows, bring-your-own LLM keys |
| Consumption (Self Serve / Scale) | Per-action metering | Web search $0.02–$0.04 per call, indexing $0.001–$0.01 per 1k tokens, retrieval $0.001–$0.01 per call, agent operations $0.001–$0.004 per run/call — across two tiers (Self Serve and Scale) |
| Enterprise — Managed | Custom + $500 starter credits | Production scaling, US/EU data residency, SOC 2, DPA, custom MSA, SSO (SAML/OIDC), audit logs, RBAC, priority support with SLAs, onboarding, architecture review |
| Enterprise — Private Hosting | Custom + $500 starter credits | Single-tenant on AWS/GCP/Azure or on-prem, Kubernetes/Compose, sovereign data residency, bring-your-own KMS/secrets/IdP, air-gapped install, dedicated solutions engineer |
LLM usage can be handled either by bringing your own provider keys or, where available, paying through Powabase. With BYO keys, model token costs are billed by the provider; Powabase platform actions remain separately metered. Early-access "free lifetime benefits" are mentioned in launch/community posts but are not defined on the pricing page; confirm the exact terms directly before relying on them.
Best For
- Agencies and product teams building new AI apps who want one backend instead of assembling Postgres + vector DB + RAG + agent runtime separately
- Developers who want the Supabase developer experience plus built-in retrieval and agent layers
- Teams using coding agents (Claude Code, Codex, Cursor) that want a backend the agent can scaffold and operate via MCP
- Regulated or sovereignty-sensitive orgs needing self-hosted, single-tenant, or air-gapped deployment
- Engineering teams in the broader AI productivity and infrastructure space evaluating an AI-native alternative to a general BaaS
FAQ
Is Powabase free?
During early access — which the pricing page currently lists as running until June 30, 2026 — the full platform is free, with per-project Postgres + pgvector, auth, storage, RAG ingestion, agents, and workflows all included. After early access, paid usage is consumption-based (metered per action). Enterprise tiers are custom-priced with $500 starter credits.
How does Powabase compare to Supabase or Firebase?
Powabase is closest to Supabase — both provide managed Postgres with auth and storage. The difference is the AI layer: pgvector, RAG ingestion, agents, and orchestration are built in rather than assembled on top. Versus Firebase, Powabase is Postgres/SQL-first rather than document-database-first.
Do I pay for LLM tokens through Powabase?
Not always. Powabase supports BYO keys for OpenAI, Anthropic, Google, and OpenRouter, with keys encrypted at rest per project, and also indicates users can pay through Powabase where available. With BYO keys, model token costs are billed by the provider; Powabase charges for platform actions (search, indexing, retrieval, agent operations) separately.
Can I self-host Powabase?
Managed Powabase Cloud is the default. Self-hosting should be described as an Enterprise Private Hosting/commercial deployment option, using Helm for Kubernetes or Compose for a single host. The private-hosting Enterprise tier adds single-tenant deployment on AWS/GCP/Azure or on-prem, sovereign data residency, and air-gapped install support.
Is Powabase open source?
The marketing FAQ raises the question but doesn't clearly answer it on the page reviewed. Confirm the licensing model directly with Powabase before assuming open-source self-host rights.
What's the RAG pipeline like?
Upload PDFs, images, office files, or URLs and Powabase extracts, chunks, embeds, and indexes them. It offers multiple indexing strategies and retrieval modes including reranking, so teams can tune retrieval rather than accept a single fixed pipeline.
Does it support coding agents and MCP?
Yes. Powabase ships native Model Context Protocol support and is optimized for Claude Code, Codex, and Cursor, so a coding agent can scaffold and operate a Powabase backend. PostgREST also exposes REST-style access to the database.
How does consumption pricing work?
Paid usage is metered per action across two tiers (Self Serve and Scale): web search $0.02–$0.04 per call, indexing $0.001–$0.01 per 1k tokens, retrieval $0.001–$0.01 per call, and agent operations $0.001–$0.004 per run/call. Benchmark a representative workload to forecast cost, since there's no flat monthly tier.
Who is Powabase not for?
Teams already running a stable Supabase + custom-RAG stack will see less marginal value. Projects that need only a vector database or only an agent framework may find the full platform's surface area more than they need. And teams that require a fixed, predictable monthly bill should account for the consumption-based model.
