LLM Orchestration

RAG AI

RAG framework for building AI-powered applications

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

A robust RAG (Retrieval-Augmented Generation) framework that enables developers to build AI-driven applications with retrieval capabilities. It simplifies the integration of large language models and data retrieval systems.

Provides a streamlined approach to integrating large language models and retrieval systems, making it easier for developers to build AI-powered applications with retrieval capabilities.

When it fits — and when it doesn’t

A good fit for

  • Teams building RAG applications who need to integrate large language models and retrieval systems efficiently

  • Projects requiring a flexible framework for AI-driven application development with retrieval capabilities

Look elsewhere if

  • Developers looking for real-time streaming capabilities (batch-only architecture)

  • Budget-constrained projects that require extensive customization or support beyond the provided features

Known weaknesses

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

  1. 01

    Limited language support beyond JavaScript and Python

    Primary focus on JS/TS and Python, no official support for other languages like Java or Go

  2. 02

    Expensive at scale due to reliance on external LLM services

    Costs associated with running large language models can escalate quickly as usage grows

What it does well

  • Simplified integration of large language models and retrieval systems

  • Support for building AI-powered applications with retrieval capabilities

  • Flexible configuration options

Pricing

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

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

Performance benchmarks

How Fast Is It?

Set up RAG AI

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

Open the setup guide →
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