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Entaoai

by Community

Chat and Ask on your own data. Accelerator to quickly upload your own enterprise data and use OpenAI services to chat to that uploaded data and ask questions

OSS

Entaoai

Added 3 Sept 2026

#azure #azure-functions #azure-openai #azure-webapp #azureopenai #chatgpt #cognitive-search #gpt-3

Overview

Entaoai is an open-source accelerator for chatting with and asking questions of your own enterprise data. It provides a TypeScript-based setup to upload data and connect it to OpenAI services for conversational retrieval. Built as a community orchestration tool, it offers a quick starting point for data chat applications.

Best for

Best for
Developers who want a quick open-source starting point for chat-on-your-data with OpenAI.

Use cases

  • Upload enterprise documents and chat with the content
  • Ask natural language questions against uploaded data
  • Prototype an OpenAI-powered data Q&A assistant

Notes

Entaoai is an open-source accelerator for chatting with and asking questions of your own enterprise data. It provides a TypeScript-based setup to upload data and connect it to OpenAI services for conversational retrieval. Built as a community orchestration tool, it offers a quick starting point for data chat applications.

866 stars on GitHub. Last updated 2025-01-02. Licensed MIT.

Use cases

  • Upload enterprise documents and chat with the content
  • Ask natural language questions against uploaded data
  • Prototype an OpenAI-powered data Q&A assistant

Pros

  • Fast to set up as an accelerator for data chat
  • Written in TypeScript for developer familiarity
  • Active community with 866 GitHub stars

Cons

  • Tied to OpenAI services for all processing
  • May require additional work for production hardening
  • Community-maintained with no formal vendor support

Indexed from awesome-langchain and enriched against its public facts.

Pros

  • Fast to set up as an accelerator for data chat
  • Written in TypeScript for developer familiarity
  • Active community with 866 GitHub stars

Cons

  • Tied to OpenAI services for all processing
  • May require additional work for production hardening
  • Community-maintained with no formal vendor support
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