7 Best Chat with your enterprise data using LLM Alternatives in 2026 (Open Source)
Chat with your enterprise data using LLM — Open-source sample for chatting with uploaded enterprise data using Azure OpenAI and vector search. vs simple PDF chatbots: enterprise Azure-native document AI platform with SQL agents, PromptFlow evaluation, speech integration, function calling, and session persistence — the most feature-rich Azure OpenAI reference implementation
Short answer
- Closest match to Chat with your enterprise data using LLM: ragflow.
- Most actively developed: ragflow (2,665 commits in the last 90 days).
- Fastest growing: ragflow (+2,412 GitHub stars in the last 30 days).
- No commit in 6+ months: knowledge-gpt and DataChad.
These 7 open-source tools do the same job. They are ordered by how closely they match Chat with your enterprise data using LLM, with live GitHub data so you can see which projects are actively maintained.
| Tool | GitHub stars | Stars / 30d | Last commit |
|---|---|---|---|
| Chat with your enterprise data using LLM(original) | 865 | 0 | 2025-01-02 |
| ragflow | 91.6k | +2,412 | 2026-10-01 |
| private-gpt | 57.6k | +57 | 2026-09-21 |
| AnythingLLM | 66.7k | +1,554 | 2026-10-01 |
| DB-GPT | 20.1k | +268 | 2026-09-28 |
| knowledge-gpt | 1.6k | -4 | 2023-09-18 |
| DataChad | 320 | -1 | 2024-02-09 |
| DocsGPT | 18.3k | +80 | 2026-10-02 |
1. ragflow
Open-source RAG engine combining knowledge retrieval and agent capabilities for LLMs
What sets it apart: Unlike LlamaIndex (framework, assemble-yourself) or AnythingLLM (desktop all-in-one), RAGFlow is a purpose-built enterprise RAG engine with deep document understanding (OCR, table extraction, layout analysis), template-based chunking with human visualization, and grounded citations — focused on quality-in-quality-out for complex enterprise documents.
Best for: Enterprises needing production RAG with deep document parsing, grounded citations, and traceable answers; Organizations with complex document types (scanned PDFs, tables, mixed formats) requiring high-fidelity extraction
2. private-gpt
Interact with your documents using the power of GPT, 100% privately, no data leaks
What sets it apart: vs LocalGPT / other private RAG: production-ready OpenAI-compatible API with LlamaIndex backend, dependency injection architecture, and enterprise upgrade path via Zylon — canonical repo (zylon-ai/private-gpt) for PrivateGPT
Best for: Regulated industries needing fully private document Q&A (healthcare, legal, finance); Teams wanting an OpenAI-compatible API for private RAG; Developers building private AI apps with production-ready primitives
3. AnythingLLM
The all-in-one AI productivity accelerator. On device and privacy first with no annoying setup or configuration.
What sets it apart: Unlike Open WebUI (chat-only) or RAGFlow (enterprise RAG focus), AnythingLLM is the most complete all-in-one desktop AI app combining RAG, no-code agent builder, MCP compatibility, multi-user support, and embeddable widgets — requiring zero coding to set up a private AI workspace.
Best for: Non-technical users who want a private, all-in-one ChatGPT replacement with document chat and agents; Small teams needing a self-hosted multi-user AI workspace with RAG and agent capabilities
4. DB-GPT
open-source agentic AI data assistant for the next generation of AI + Data products.
What sets it apart: Full-stack AI data assistant combining autonomous SQL generation, sandboxed code execution, and reusable skills in a single platform — not just a chatbot
Best for: Data teams needing natural language database querying; Organizations wanting AI-powered data analysis assistants; Teams building data-driven agent workflows
5. knowledge-gpt
Accurate answers and instant citations for your documents.
What sets it apart: vs ChatPDF/Unstructured: simple Streamlit-based document Q&A with citation extraction — optimized for quick single-document analysis with verifiable source references
Best for: Extracting cited answers from research papers and reports; Quick document Q&A with source verification; Prototyping RAG-based document analysis tools
6. DataChad
Ask questions about any data source by leveraging langchains
What sets it apart: vs generic RAG chatbots: combines vector embeddings with Smart FAQ curation and context display — shows exactly which chunks informed each answer for transparency
Best for: Quick knowledge base creation from documents and URLs; Conversational Q&A over custom datasets; Building intelligent FAQ systems from existing content
7. DocsGPT
Private AI platform for agents, assistants and enterprise search. Built-in Agent Builder, Deep research, Document analysis, Multi-model support, and API connectivity for agents.
Best for: Enterprise teams building private document Q&A systems; Organizations needing on-premise AI deployment with data privacy control; Teams requiring multi-format document ingestion including audio workflows
FAQ
- What are the best alternatives to Chat with your enterprise data using LLM?
- The closest open-source alternatives to Chat with your enterprise data using LLM are ragflow, private-gpt and AnythingLLM, followed by DB-GPT, knowledge-gpt and DataChad. They are ranked by how closely they match what Chat with your enterprise data using LLM does.
- Which Chat with your enterprise data using LLM alternative is the most popular?
- ragflow has the most GitHub stars among Chat with your enterprise data using LLM alternatives, with 91,600 stars.
- Which Chat with your enterprise data using LLM alternative is the most actively maintained?
- By recent activity, ragflow (2,665 commits in the last 90 days) is the most actively developed alternative.