triggerdotdev/trigger.dev Alternatives

Python agent framework; choose if you want to build agents in Python without durable task infrastructure.

The agent that grows with you

Python agent harness with planning and tools; choose for a lightweight self-hosted personal assistant without managed scaling.

Open-source super AI assistant & Agent Harness. Plans tasks, runs tools and skills, self-evolves with memory and knowledge. Multi-agent, multi-model, multi-channel. Lightweight, extensible, one-line install. (formerly chatgpt-on-wechat)

Python multi-agent framework from OpenAI; choose for simple agent loops with OpenAI services, not for long-running durable workflows.

A lightweight, powerful framework for multi-agent workflows

LangChain-based agent harness; choose for quick agent prototyping in Python instead of a deployed workflow platform.

The batteries-included agent harness.

Google's code-first agent toolkit; choose for flexibility in agent development, but it lacks built-in durable execution.

An open-source, code-first Python toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control.

Enterprise Java agent workflow platform; choose if your stack is Java and you need similar orchestration with commercial support.

Enterprise-grade, commercial-friendly agentic workflow platform for building next-generation SuperAgents.

Python framework for autonomous agent crews; choose for simple multi-agent autonomy in Python, not durable serverless execution.

PraisonAI 🦞 — Hire a 24/7 AI Workforce. Stop writing boilerplate and start shipping autonomous self-improving agents that research, plan, code, and execute tasks. Deployed in 5 lines of code with built-in memory, RAG, and support for 100+ LLMs.

Memory-first agent harness; choose for self-improving research agents in Python rather than a managed deployment platform.

The Harness of Harnesses: a trusted, persistent, self-evolving multi-agent ecosystem for all-domain collaboration.

Go-based agent platform with multi-tenant isolation; choose if you need Go concurrency and heavy resource control for agent teams.

GoClaw - GoClaw is OpenClaw rebuilt in Go — with multi-tenant isolation, 5-layer security, and native concurrency. Deploy AI agent teams at scale without compromising on safety.

Rust-core agent framework with Python wrapper; choose for performance-critical agent workloads over managed workflows.

GraphBit is the world’s first enterprise-grade Agentic AI framework, built on a Rust core with a Python wrapper for unmatched speed, security, and scalability. It enables reliable multi-agent workflows with minimal CPU and memory usage, making it production-ready for real-world enterprise environments.

Go agent framework with MCP tooling; choose for Go-native agent orchestration without deployed queues.

Open-source Agentic AI framework in Go for building, orchestrating, and deploying intelligent agents. LLM-agnostic, event-driven, with multi-agent workflows, MCP tool discovery, and production-grade observability.

LangGraph-based graph orchestration framework; choose if you want graph-defined agent loops and Dify DSL conversion rather than a full platform.

Graph-Orchestrated Agent Loop — a production-grade framework on LangGraph. Combine workflow graphs and agent loops, transpile Dify DSL to runnable code, swap wire protocols (Dify/OpenAI).

Python personal agent framework with WebUI; choose for a lightweight self-hosted agent with tools and memory, not a scalable workflow service.

Ultra-lightweight, open-source, self-hosted personal AI agent framework in Python with WebUI, tools, memory, MCP, multi-agent workflows, automation, and chat apps

Production multi-agent harness in Python; choose for building agent teams, but without durable queues and retries.

Multi-Agent Harness for Production AI

Self-hosted knowledge agent platform with RAG and multi-agent; choose for knowledge-focused agents with built-in sandbox and governance.

可私有部署的多租户知识智能体平台：统一 RAG、知识图谱、多智能体、MCP/Skills、沙盒与权限管理。Self-hosted knowledge agent platform for RAG, knowledge graphs and multi-agent workflows.

Java framework for distributed long-running agents; choose if your team is JVM-centric and needs durable agent execution.

Build distributed, production-grade, long-running agents.

Microsoft framework for AI agents on Python/.NET; choose for cross-language agent building, but lacks built-in serverless tasks.

A framework for building, orchestrating and deploying AI agents and multi-agent workflows with support for Python and .NET.

Older TypeScript agent platform; a previous-generation alternative if you need a simple in-house deployment without current maintenance.

Evo AI is an open-source platform for creating and managing AI agents, enabling integration with different AI models and services.

PHP durable workflow engine; choose for long-running workflows in PHP, narrower than an AI agent platform.

Core package for defining and running durable workflows and activities. Supports long-running persistent workflows, retries, queues, parallel execution, workflow monitoring, dedicated storage connections, and orchestration for microservices, data pipelines, sagas, agentic workflows, and other complex business processes.

Lightweight TypeScript workflow engine; choose for simple orchestration needs without AI agent or scaling features.

A lightweight workflow engine

Ready-to-use personal AI assistant app; use as an end-user tool, not a library to embed in your own workflows.

⚡️next-generation personal AI assistant powered by LLM, RAG and agent loops, supporting computer-use, browser-use and coding agent, demo: https://demo.openagentai.org

Low-code GUI platform for agent workflows; choose if you want a visual builder over a code-first SDK.

Build Agentic workflows, RAG pipelines, with rich AI model and tool support on one collaborative workspace. Deploy on cloud, VPC, or self-hosted, so teams move from prototype to production without rebuilding the stack.

Installable personal AI assistant app; use directly as an end-user assistant, not as a workflow engine.

Your Personal AI Assistant; easy to install, deploy on your own machine or on the cloud; supports multiple chat apps with easily extensible capabilities.