raggenie

raggenie

RAGgenie is a low-code platform for building retrieval-augmented generation (RAG) conversational AI 'copilots' from your existing data, enabling teams and individuals to create, run locally, and integrate custom GenAI assistants without advanced technical skills.

raggenie is chatbots & assistants software teams evaluate for chatbots & assistants. Use this page to review pricing, integration signals, and the best alternatives before you commit.

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One of 175 tools in Chatbots & Assistants
Added 2 months ago
Data reviewed Sep 10, 2026

Profile facts come from the vendor source. AiMatch labels unknown pricing or API details instead of estimating them.

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Quick Overview

Best for: Chatbots & Assistants

What it does

Chatbots & Assistants software for decision-makers comparing workflow fit and alternatives.

Best fit

Chatbots & Assistants

Pricing snapshot

Pricing available on request

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RAGgenie is a low-code RAG (retrieval-augmented generation) builder that enables users to create conversational AI copilots from their existing data without requiring advanced technical skills. The platform emphasizes ease-of-use: you can chat with databases in plain language and build custom conversational AI apps quickly. RAGgenie is offered as an open-source tool with guidance for running locally, and provides community channels (GitHub, Slack), demo resources, and connectors to integrate with team tools and external apps.

Low-code platform to build custom GenAI copilots using your data.

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Key Features

Low-code RAG builder

Build conversational AI apps and copilots with minimal or no coding using a low-code platform.

Natural language database chat

Chat with your database in plain language to retrieve and interact with information.

Out-of-the-box connectors

A connectors directory to link your team’s favorite tools for data and workflow integration.

Open-source and local deployment

Guides for running RAGgenie locally and an open-source codebase to customize deployments.

Tutorials and demo resources

Tutorial videos and demo sessions to learn how to build and run GenAI copilots.

Pricing

Current pricing details are not available from the vendor source.

Use Cases

Create custom GenAI copilots

Use your own data to build conversational assistants tailored to specific tasks or knowledge domains.

Embed conversational AI into apps

Integrate generated copilots into existing applications to provide natural-language access to data and workflows.

Team knowledge access

Connect team tools and data sources so teams can query and collaborate over shared information.

Local development and experimentation

Run RAGgenie locally to develop, test, and customize copilots using provided guides and the open-source project.

Integrations

Connectors directory

Out-of-the-box connectors to link data sources and third-party tools so teams can integrate RAGgenie into existing workflows.

Benefits

Rapid creation of conversational AI copilots without advanced technical skills
Reuse of existing organizational data to power assistants
Prebuilt connectors simplify integration with team tools and workflows
Open-source codebase and local-run guides enable customization and control
Community channels (GitHub, Slack) and demo/tutorial resources support adoption

Limitations

Early adopter seats are limited ("Please note that these seats are limited.")

Frequently Asked Questions

No verified FAQs are available.

Getting Started

  1. 1 Step 1: Visit the RAGgenie site and review demo and tutorial resources.
  2. 2 Step 2: Connect your data sources using the connectors directory to provide content for your copilot.
  3. 3 Step 3: Build a copilot via the low-code interface or follow the guide to run RAGgenie locally; join the community or book a demo for support.

Support

docs

Tutorial videos and guides available on the site to learn how to build and run RAGgenie.

demo

Book a Demo option to see the platform and obtain guided assistance.

community

Collaborative GitHub community and Slack workspace for discussion, support, and development.

API

Available: No

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