LLM Orchestration

RAG AI Backend

Backend framework for Retrieval-Augmented Generation applications.

Status
Generally available
Last checked
Checked · Oct 12, 2026
License
Proprietary
Pricing
Free tier
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What it is

A backend framework designed to power Retrieval-Augmented Generation (RAG) applications, enabling developers to build AI-driven apps that retrieve and generate content efficiently. It is particularly useful for teams looking to integrate RAG capabilities into their existing systems without the need for extensive setup or maintenance.

The only RAG framework offering a self-hosted solution for efficient retrieval-augmented generation, tailored specifically for JavaScript/TypeScript ecosystems.

When it fits — and when it doesn’t

A good fit for

  • Teams building RAG applications who need a self-hosted backend solution

  • Projects requiring integration of RAG capabilities into existing JavaScript/TypeScript systems

  • Developers looking for an efficient way to implement retrieval-augmented generation without cloud dependencies

Look elsewhere if

  • Applications that require real-time streaming data processing (batch-only architecture)

  • Teams with limited technical expertise in self-hosting and maintaining backend services

Known weaknesses

Each one links to the public issue, changelog or docs page it came from, where we have one.

  1. 01

    Limited integrations with other RAG tools and platforms

    Documentation lacks examples for integrating with popular RAG systems like LangChain or LlamaIndex

What it does well

  • Efficient retrieval and generation capabilities for RAG applications

  • Self-hosted backend framework to integrate with existing systems

  • Supports both JavaScript and TypeScript

Pricing

Free tier
Yes
Paid from
—
Model
Flat rate
Enterprise plan
No

Pricing not independently confirmed — check the vendor’s page.

Performance benchmarks

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Set up RAG AI Backend

Setup steps, common gotchas and what to check after 30 days.

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