Accelerator

RAGLite

A lightweight, high-performance Python toolkit to streamline RAG workflows.

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Build smarter RAG applications.
Faster.

RAGLite is a lightweight, high-performance Python toolkit that simplifies Retrieval-Augmented Generation (RAG) workflows. It helps teams deliver scalable, efficient, and accurate AI systems, without the complexity of traditional stacks.

Why choose RAGLite

Simplify your RAG stack

RAGLite replaces complex RAG toolchains with one unified Python toolkit, covering ingestion, chunking, hybrid search, reranking, generation, and UI. No external frameworks needed.

RAGLite replaces complex RAG toolchains with one unified Python toolkit, covering ingestion, chunking, hybrid search, reranking, generation, and UI. No external frameworks needed.

Deploy in one command

No more managing frontends, backends, databases, or glue code. With one CLI command, RAGLite handles document ingestion, evaluation, benchmarking, and integrates with Chainlit and Claude MCP, powered by a single, portable database file.

State-of-the-art retrieval quality

RAGLite is engineered for retrieval accuracy, not just speed. It uses semantic chunking, contextual headings, multi-vector embeddings, hybrid search, late chunking, and reranking to deliver relevant, high-quality results out of the box.

Smarter results, seamless UX

RAGLite goes beyond basic retrieval. It adapts to query intent with intelligent pipelines, leveraging adaptive LLMs to select optimal retrieval strategies. Combined with Chainlit and Claude, it supports reasoning, citations, and tool use, all in a unified workflow.

RAGLite updates

RAGLite updates

RAGLite updates

Built for engineers. Ready for production.

Python-native

Python-native

Python-native

No proprietary formats or third-party orchestration.

Lightweight & fast:

Designed for performance without overhead.

Modular

Modular

Modular

Use it end-to-end or integrate into existing workflows.

Open source

Open source

Open source

Actively maintained on GitHub with transparent development and community contributions, giving you full visibility and control.

operational value chain analyzed with AI
operational value chain analyzed with AI
operational value chain analyzed with AI

RAGLite features

Configurable

Configurable

Configurable

Fast and permissive

Fast and permissive

Fast and permissive

Unhobbled

Unhobbled

Unhobbled

Extensible

Extensible

Extensible

RAGLite insights

RAGLite tutorial

Article

This guide walks you through the process of building a powerful RAG pipeline using RAGLite. From configuring your LLM and database to implementing advanced retrieval strategies like semantic chunking and reranking, this guide covers everything you need to optimize and scale your RAG-based applications.

RAGLite tutorial

Article

This guide walks you through the process of building a powerful RAG pipeline using RAGLite. From configuring your LLM and database to implementing advanced retrieval strategies like semantic chunking and reranking, this guide covers everything you need to optimize and scale your RAG-based applications.

RAGLite tutorial

Article

This guide walks you through the process of building a powerful RAG pipeline using RAGLite. From configuring your LLM and database to implementing advanced retrieval strategies like semantic chunking and reranking, this guide covers everything you need to optimize and scale your RAG-based applications.

RAGLite

Article

Discover RAGLite, a lightweight toolkit that revolutionizes Retrieval-Augmented Generation (RAG). With features like semantic chunking, adaptive retrieval, and hybrid search, RAGLite overcomes traditional RAG limitations, simplifying workflows and ensuring fast, scalable, and accurate information retrieval for real-world AI applications.

RAGLite

Article

Discover RAGLite, a lightweight toolkit that revolutionizes Retrieval-Augmented Generation (RAG). With features like semantic chunking, adaptive retrieval, and hybrid search, RAGLite overcomes traditional RAG limitations, simplifying workflows and ensuring fast, scalable, and accurate information retrieval for real-world AI applications.

RAGLite

Article

Discover RAGLite, a lightweight toolkit that revolutionizes Retrieval-Augmented Generation (RAG). With features like semantic chunking, adaptive retrieval, and hybrid search, RAGLite overcomes traditional RAG limitations, simplifying workflows and ensuring fast, scalable, and accurate information retrieval for real-world AI applications.

Ready to get started?

Start building RAG today with RAGLite

Because your time is better spent innovating, not configuring!

Whether you're an engineer building your first RAG pipeline or an executive scaling enterprise AI, RAGLite gives you the tools to move faster, with less friction.

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Locations

Brussels HQ

Central Gate

Cantersteen 47



1000 Brussels

Ghent

Planet Group Arena

Ottergemsesteenweg-Zuid 808 b300

9000 Gent

© 2024 Superlinear. All rights reserved.

Locations

Brussels HQ

Central Gate

Cantersteen 47



1000 Brussels

Ghent

Planet Group Arena
Ottergemsesteenweg-Zuid 808 b300
9000 Gent

© 2024 Superlinear. All rights reserved.

Locations

Brussels HQ

Central Gate

Cantersteen 47



1000 Brussels

Ghent

Planet Group Arena
Ottergemsesteenweg-Zuid 808 b300
9000 Gent

© 2024 Superlinear. All rights reserved.