Postgres, RAG, and agents. One backend.

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June 12, 2026

Powabase

United States Backend development

5.0(1)

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5.0(1)

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Postgres, RAG, and agents. One backend.

Local Open Source AI Development Platform AI Development Postgres Data Storage

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Powabase is the all-in-one development platform for AI apps. Comes with RAG, agents, drag & drop workflows. Fine-tuned for AI coding agents.

What makes Powabase different

- RAG out of the box: Embeddings, vector search, and retrieval pipelines are first-class citizens — not bolt-ons. Build semantic search and grounded AI features on your own data in minutes.
- Agents, built in: Define, run, and orchestrate AI agents natively on the platform. No glue code, no separate orchestration layer — your data, your logic, and your agents all live in one place.
- Drag & drop workflows: Compose powerful AI pipelines visually. Connect data, models, and actions on a canvas anyone on your team can understand and iterate on.
- Fine-tuned for AI coding agents: Powabase is purpose-built to be driven by AI coding assistants. Clean, predictable APIs, agent skills (npx skills add powabase-ai/agent-skills), and an MCP server mean your agents generate working backends correctly, with minimal token waste and iteration.

Underneath the AI layer sits everything you expect from a serious platform: real open-source Postgres, instant auto-generated APIs, built-in auth and storage, and a polished Studio to manage it all. Open, portable, and self-hostable.

Spin up isolated projects in seconds, wire up RAG and agents through a unified control plane, and deploy with confidence. Powabase collapses the entire AI stack — database, retrieval, agents, and workflows — into one cohesive platform.

Powabase — the fastest way to build, ship, and scale AI apps.

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June 12, 2026

Initial release of Powabase.

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Backend development Powabase

United States Backend development

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Pros and Cons

Pros

Own Postgres per project

Rich toolkit: storage, auth

Realtime capabilities

Out-of-the-box document extraction

Embedding and indexing features

HTTP or MCP agent calls

Option for self-hosting

Single REST API convenience

Provides an auth service

Offers object storage

Robust backend system

RAG for document retrieval

Supports large language models

Visual and callable workflows

Isolated stack per project

Compliant environment by default

Flexible deployment options

Supports multiple knowledge bases

PDF, image and URL support

Multimodal content indexing

Web search and code execute

Drag and connect workflow blocks

No shared logical databases

Cloud and personal infrastructure options

Works with Claude Code Codex

Customizable deployment options

OCR with 91% accuracy

RAG pipeline with 98.7% accuracy

Realtime access through PostgREST

Supports multiple LLMs

Integrated track multi-turn state

Efficient RAG payloads

Supports Docker or Kubernetes

Built-in SOC 2 / HIPAA compliance

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Cons

Few out-of-the-box agent tools

Self hosting requires technical expertise

Limited templates for prompts and example apps

Requires database knowledge

Not a "DIY AI chatbot builder"

No direct voice integration

Complex for beginners

Requires coding knowledge

Limited language support

Limited third-party integrations

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Q&A

What is Powabase?

Powabase is a comprehensive development platform designed for AI applications. It provides each project with its own set of tools, such as Postgres, storage, authentication, realtime services, and an agent runtime. The platform not only supports complex, AI-based applications but also assists developers by simplifying the creation process. Powabase facilitates system descriptions, then wires up the retrieval, agents, and workflows behind a single REST API, significantly reducing the need for intricate code-writing.

How does Powabase handle document extraction and indexing?

Powabase employs its Retrieval, Agents, and Generators (RAG) pipeline for document extraction and indexing. Whenever a document is uploaded to Powabase, the RAG pipeline takes over and carries out a seamless extraction, embedding, and indexing of the document content. This feature automates the process, freeing up developers from manual extraction and indexing tasks.

What is RAG in Powabase?

RAG in Powabase stands for Retrieval, Agents, and Generators. It is a crucial part of the platform geared towards enhancing document handling and processing. The RAG pipeline is responsible for extracting, chunking, embedding, and indexing the uploaded content, which can vary from PDFs and images to office files and URLs.

How can developers create AI-native apps with Powabase?

Developers can create AI-native apps with Powabase by describing what they aim to achieve. The platform then autonomously wires up the retrieval, agents, and workflows behind a single REST API. It's geared towards enhancing ease of usage and providing an effortless development experience. The developers don't need to worry about the technicalities; they simply need to state their requirement, and Powabase constructs the necessary mechanisms behind the scenes.

What backend services does Powabase offer?

Powabase offers a robust set of backend services to developers. These services encompass Postgres databases, object storage, and realtime services. Additionally, Powabase also provides a first-class authentication service accessible through PostgREST, achieving security and access management. All these services can either be directly accessed or through the REST/GraphQL-style API of Powabase.

How does Powabase enhance document retrieval?

To enhance document retrieval, Powabase uses its unique RAG pipeline, which performs the extraction, chunking, embedding, and indexing of uploaded content. It also has built-in retrieval events and tool calls that aid in swiftly locating and accessing stored information.

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What type of content can Powabase process?

Powabase is capable of processing various types of content, including PDFs, images, office files, and URLs. It utilizes its RAG pipeline to extract, chunk, embed, and index these various formats into a readable and easily accessible structure.

How can developers define orchestrations with Multiple Large Language Models in Powabase?

Developers can define orchestrations with multiple Large Language Models (LLMs) in Powabase. They use ReAct orchestrations, which can bring together multiple LLMs, knowledge bases, and tools. These orchestrated setups drive the response to retrieval events, initiate tool calls, handle token deltas, and manage citations, generating efficient AI workflows.

What are the benefits of the visual workflows in Powabase?

The visual workflows in Powabase have multiple benefits. They enable developers to construct multi-step workflows by simply dragging and connecting different blocks comprising triggers, conditions, and agents. These workflows are not just visual but also callable, promoting easy understanding and convenient code-writing. They also empower developers to transform natural-language requirements into functional workflow blocks

What is the purpose of the isolated stack in every Powabase project?

An isolated stack in every Powabase project is allocated to guarantee data integrity and security. It confirms that there are no shared logical databases, eliminating potential risk situations. It also helps to default to various compliance standards, such as SOC 2 and HIPAA, enhancing the platform's safety and trustworthiness.

What deployment options does Powabase provide?

Powabase offers flexible deployment options. Users have the freedom to operate their projects on Powabase's cloud, or they can opt to run the entire stack on their own infrastructure. This flexibility means users can tailor the deployment to best suit their operational needs and preferences.

Does Powabase support self-hosting?

Yes, Powabase does support self-hosting. The platform allows for easy transfer between Powabase's services and independent hosting, giving freedom to the developers to maintain and manage their own infrastructure.

What kind of storage does Powabase offer?

Powabase provides object storage as part of its platform offering. This storage is exclusive to each project, ensuring data isolation and minimizing cross-interference risks. The storage can be accessed directly or via the REST/GraphQL-style API provided by Powabase.

Does Powabase have an auth service?

Yes, Powabase provides an authentication service. This service presents a secure way of managing access to the platform's resources. The auth service supports a security-first approach and can easily be accessed through PostgREST, ensuring that platform resources remain accessible only to authenticated users.

What are Powabase agents and how do they work?

Powabase agents are a critical part of the platform's operation. They are responsive to HTTP and MCP calls and can either be self-hosted or used via Powabase's services. These agents interact with the tools in the response to retrieval events, participating in tool calls, managing token deltas, and overseeing citations. They thus form a fundamental part of the platform's data processing and managing mechanisms.

How does Powabase support multiple Large Language Models (LLMs)?

Powabase supports multiple Large Language Models (LLMs) by allowing developers to define orchestrations that incorporate multiple LLMs, along with knowledge bases and tools. These orchestrations drive the platform's response to retrieval events, tool calls, token deltas, and citations, helping create highly efficient AI workflows.

What is the role of triggers, conditions, and agents in Powabase's visual workflows?

Triggers, conditions, and agents are critical elements in Powabase's visual workflows. Developers can create sophisticated workflows by dragging and connecting these building blocks. While triggers initiate a workflow, conditions define the criteria under which specific workflows or tasks are carried out, and agents manage the necessary steps or actions. This structured arrangement of operations provides developers with a visual, easy-to-understand, and simplified interface for creating complex workflows.

In what formats can content be uploaded for processing on Powabase?

Content in Powabase can be uploaded for processing in multiple formats like PDFs, images, office files, or URLs. This flexibility allows for a wide range of data types to be ingested and utilized in the platform.

How can Powabase be used to develop AI-native apps?

Developers can use Powabase to develop AI-native apps by merely describing what they want the app to do. Powabase, with its advanced backend mechanisms, will then wire up the necessary retrievals, agents, and workflows behind a single REST API, allowing developers to focus more on the app's functionality rather than intricate backend details.

Does Powabase allow on-premises deployment?

Yes, Powabase allows on-premises deployment. It enables users to run the entire stack on their own infrastructure, thereby giving them control over their systems while still availing themselves of all the platform's robust features.

What is Powabase specifically designed for?

Powabase is specifically designed as a comprehensive development platform for AI applications.

What are the unique tools each Powabase project comes with?

Every Powabase project is equipped with a unique set of tools, including Postgres, storage, auth, realtime, and an agent runtime.

What functionalities come with Powabase out of the box?

Powabase comes out of the box with Retrieval, Agents, and Generators (RAG), plus, it has features for document extraction, embedding, and indexing upon upload.

How does Powabase handle document extraction and embedding?

Powabase utilizes its RAG pipeline to handle document extraction and embedding. When a user uploads a document, the system extracts, chunks, embeds, and indexes it automatically.

Mention some ways the Powabase agents can be used?

Powabase agents can be used to call tools over HTTP or MCP. These agents can easily be self-hosted or used via the platform's services.

What is the specialty of the Powabase AI coding agents?

The specialty of Powabase AI coding agents lies in their ability to natively interact with the platform. Once the Powabase skill is installed, these AI coding agents can directly set up retrieval, agents, and workflows based on described needs.

How does Powabase support the creation of AI-native apps?

Powabase supports the creation of AI-native apps by allowing developers to describe what they want upon which the platform automatically wires up essential components like retrieval, agents, and workflows behind a single REST API.

What is the role of Powabase's backend system for my apps?

Powabase's robust backend provides necessary support for your apps by offering a full suite including a Postgres with RLS, a high-grade auth service, object storage, and real-time access.

How does Powabase enhance document retrieval?

Powabase enhances document retrieval with its out-of-the-box RAG pipeline. This pipeline ensures seamless processing of uploaded documents through extraction, chunking, embedding, and indexing.

What forms of content does Powabase support for upload?

Powabase supports a variety of content forms for upload including PDFs, images, office files, and URLs.

How can developers define orchestrations with Powabase?

Developers can define orchestrations with Powabase by using multiple Large Language Models (LLMs), knowledge bases, and tools with built-in retrieval events, tool calls, token deltas, and citations.

Could you give some examples of Powabase's built-in retrieval events?

Powabase's retrieval events are logged during the run of ReAct orchestrations. As multiple LLMs, knowledge bases, and tools run over SSE, all retrieval events, tool calls, token deltas, and citations get fully logged.

How does Powabase handle workflow design?

With Powabase, multi-step workflows can be built by dragging and connecting blocks such as triggers, conditions, and agents. The workflow design also supports a natural language copilot.

How does Powabase ensure project data isolation?

Powabase ensures project data isolation by providing each project with its own isolated stack. This ensures no shared logical databases and default compliance.

What are Powabase's deployment options?

Powabase provides flexible deployment options, including running projects on Powabase's cloud or on users' own infrastructure.

What are the benefits of using Powabase for AI development?

The benefits of using Powabase for AI development include reduced build costs, faster process from zero to a working product, native support for AI apps, streamlined workflows, compliance by default, and optimized agent setups.

How does Powabase approach object storage and indexing for uploaded files?

Powabase uses its RAG pipeline to manage object storage and indexing for uploaded files. As part of the process, the files are extracted, chunked, embedded, and then indexed on the platform to facilitate efficient retrieval and data handling.

How versatile is Powabase's drag & drop interface for building agent workflows?

Powabase's drag and drop interface for building agent workflows is highly versatile. Developers can build multi-step workflows by dragging and connecting blocks. It is also assisted by a natural language copilot for more user-friendly design.

We often deal with compliance issues. How does Powabase handle that?

Powabase handles compliance issues by providing an isolated backend for each project. This prevents any shared logical databases, minimizes the risk of data interference, and ensures compliance with standards such as SOC 2, ISO 27001, and HIPAA.

What are the possible modes of using Powabase: managed cloud, self-hosted or a hybrid?

Powabase can be used in three different modes: as a fully-managed cloud solution, run it as a self-hosted solution on your own infrastructure, or a hybrid model where you can use Powabase cloud while bringing your own LLM keys for cost and compliance control.

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