8 Best LLMStack Alternatives in 2026 (Open Source)

LLMStack — No-code multi-agent framework to build LLM Agents, workflows and applications with your data. vs Flowise / Dify: no-code AI platform with multi-tenant support, built-in vector DB, and Slack/Discord integration — deploy AI agents from Google Drive/Notion data without writing code

These 8 open-source tools do the same job. They are ordered by how closely they match LLMStack, with live GitHub data so you can see which projects are actively maintained.

ToolGitHub starsStars / 30dLast commit
LLMStack(original)2.3k+22024-12-11
Dify157.6k+3,6682026-09-30
Flowise55.5k+6972026-08-13
Langflow155.4k+1,4572026-09-29
iX1.0k+02024-03-03
Dust1.5k+262026-09-30
TaskingAI5.4k+42024-10-31
Flock1.1k+42026-07-06
Chaindesk3.0k+42024-06-17

  1. 1. Dify

    Production-ready platform for agentic workflow development.

    What sets it apart: Unlike LangGraph (code-first orchestration), Dify offers a complete visual IDE combining workflow builder, RAG pipeline, prompt engineering, and production monitoring in one platform — the Vercel of LLM apps

    Best for: Teams building RAG-powered chatbots and AI apps with visual workflow and no backend coding; Product teams who need LLMOps monitoring alongside app development in one platform

    ⭐ 157.6kLLMStack vs Dify →Full profile →

  2. 2. Flowise

    Build AI Agents, Visually

    What sets it apart: Easiest no-code AI agent builder with one-command setup (npx flowise start) — simpler than Langflow, targeting non-developers who want AI workflows without Python

    Best for: Non-technical users building AI chatbots and RAG applications; Quick prototyping of LLM workflows with drag-and-drop

    ⭐ 55.5kLLMStack vs Flowise →Full profile →

  3. 3. Langflow

    Langflow is a powerful tool for building and deploying AI-powered agents and workflows.

    What sets it apart: Best visual builder for LLM workflows with direct MCP server deployment — more production-ready than Flowise with API-first architecture

    Best for: Rapid prototyping of AI agent workflows with visual builder; Non-developers building LLM applications without coding

    ⭐ 155.4kLLMStack vs Langflow →Full profile →

  4. 4. iX

    Autonomous GPT-4 agent platform

    What sets it apart: vs LangChain/AutoGen: visual no-code drag-and-drop editor with native multi-agent orchestration and horizontal worker scaling — design complex agent workflows visually instead of writing code

    Best for: Building custom multi-agent teams with visual no-code editor; Rapid prototyping of AI workflows without coding; Organizations needing self-hosted parallel agent execution at scale

    ⭐ 1.0kLLMStack vs iX →Full profile →

  5. 5. Dust

    Custom AI agent platform to speed up your work.

    What sets it apart: Enterprise AI agent platform that connects to company knowledge bases (Slack, Notion, Drive) — unlike developer-focused frameworks, Dust is designed for non-technical teams to build and deploy custom AI agents

    Best for: Enterprise teams wanting custom AI agents connected to internal data; Organizations needing managed AI agent platform with team collaboration

    ⭐ 1.5kLLMStack vs Dust →Full profile →

  6. 6. TaskingAI

    The open source platform for AI-native application development.

    What sets it apart: BaaS platform for LLM agent development with unified API across hundreds of models, decoupled modular management of tools/RAG/models, and one-click production deployment

    Best for: llm-app-backend-service; multi-tenant-ai-platforms; unified-multi-model-management

    ⭐ 5.4kLLMStack vs TaskingAI →Full profile →

  7. 7. Flock

    Flock is a workflow-based low-code platform for rapidly building chatbots, RAG, and coordinating multi-agent teams, powered by LangGraph, Langchain, FastAPI, and NextJS.（Flock 是一个基于workflow工作流的低代码平台，用

    What sets it apart: vs Dify/Flowise: native human-in-the-loop approval, subgraph nodes for modular reuse, and MCP protocol support for flexible tool integration

    Best for: Teams building conversational AI with visual workflow design; Organizations needing human-in-the-loop agent workflows

    ⭐ 1.1kLLMStack vs Flock →Full profile →

  8. 8. Chaindesk

    The no-code platform for building custom LLM Agents

    What sets it apart: vs Botpress/Voiceflow: no-code LLM agent builder with semantic search — evolved into Chaindesk managed platform for production chatbot deployment

    Best for: Non-technical users wanting to build LLM-powered chatbots; Quick customer support bot prototyping; Teams evaluating no-code LLM agent platforms

    ⭐ 3.0kLLMStack vs Chaindesk →Full profile →