YuanASI
Delivering AI Agents from POC to enterprise production processes through a controllable, inspectable, and TypeScript-native orchestration engine.
At a Glance
- Enterprise IT and backend development teams
- AI engineering startups
- Companies requiring on-premise or private AI infrastructure
- TypeScript and Node.js developers
AI Tools by YuanASI
(1)
Open Multi-Agent
AI Agent Orchestration Framework
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Latest News
Released Open Multi-Agent v1.13.0 with release guide and OTel adapter documentation
Published framework comparison guide: LangGraph, CrewAI, AutoGen vs. Open Multi-Agent
Published engineering note: When to move from low-code platforms (Dify, Coze) to code-level frameworks
Published analysis on why AI Agent projects fail and how to avoid common pitfalls
Products & Services
A TypeScript-native orchestration framework for Node.js backends. It allows specialist AI agents to work as a team using task DAGs, parallel execution, and a built-in Run Viewer for observability.
Customized development service for building high-frequency, rule-clear business process automation using AI agents.
Engineering services to integrate multi-agent systems with enterprise software (CRM, ERP, internal APIs) and RAG knowledge bases.
Consulting services for AI scenario evaluation, tech selection, POC development, and ROI assessment.
Market Position
Positions itself as a production-ready, TypeScript-native alternative to Python-based frameworks like LangGraph and CrewAI, emphasizing stability, controllability, and integration ease for web-scale backends.
Leadership
Founders
Chen Kaijie (Jack Chen)
Creator of the Open Multi-Agent framework. Has a background in product management and AI engineering. Educated at Shenzhen University. Known for his work on TypeScript-native AI orchestration.
Executive Team
Chen Kaijie (Jack Chen)
Founder & CEO
Founder of YuanASI and lead creator of the Open Multi-Agent framework. Focuses on bridging the gap between AI POCs and production-grade systems.
Founding Story
YuanASI was founded to address the challenges of moving AI agents from experimental demos to stable production systems. The vision was to create an orchestration layer that provides the same level of control and auditability as traditional software engineering, leading to the development of the Open Multi-Agent framework.
Business Model
Revenue Model
Project-based consulting, customized software development, and system integration services focused on the deployment of AI agent systems for enterprise clients.
Target Markets
- Enterprise IT and backend development teams
- AI engineering startups
- Companies requiring on-premise or private AI infrastructure
- TypeScript and Node.js developers
- Automated contract review and legal document analysis
- Multi-step market research and report generation
- High-frequency customer service ticket automation
- Complex enterprise workflow orchestration (e.g., CRM/ERP automation)
- Internal tool development for TypeScript/Node.js environments
- temodar-agent