AG2 provides a platform for building, orchestrating, and evolving systems of AI agents that function as an enterprise‑scale AI workforce. Its AgentOS runtime unifies agents from multiple frameworks—including AG2, Google ADK, OpenAI, and LangChain—into coordinated teams using standardized protocols and built‑in security, enabling organizations to integrate specialized AI personas into cohesive workflows. The solution is open source at its core and packaged for enterprise deployment.
Funding
Funding not disclosed
Founders
Product
Problem
Enterprises and developers face fragmented AI tooling, requiring separate integrations for each large‑language model or agent framework, which hampers the creation of coordinated, production‑grade multi‑agent systems. This siloed approach leads to higher engineering overhead, limited scalability, and difficulty ensuring security and auditability across heterogeneous agents.
Solution
AG2 offers a unified platform—AgentOS—that serves as a runtime for building, orchestrating, and evolving networks of AI agents at enterprise scale. By supporting agents from AG2’s own suite, Google ADK, OpenAI, and LangChain, the platform enables cross‑platform coordination through standardized A2A and MCP protocols with built‑in security. Developers can assemble dynamic teams of specialized personas using a visual Studio interface, while the Orchestrator manages task distribution, parallel execution, and traceability. The open‑source core provides flexibility for customization, and the enterprise‑ready infrastructure ensures scalability, auditability, and compliance for production deployments.
Target Audience
Primary customers are enterprise AI engineering teams, platform developers, and research groups that need to build and manage large‑scale, multi‑agent AI applications.
Features
- Universal framework interoperability that connects agents from multiple providers into a single cohesive team
- Standardized A2A and MCP communication protocols with enterprise‑grade security and audit logs
- Visual Studio for designing, testing, and deploying agent workflows without extensive code
- Parallel execution engine that accelerates workflows up to 5× and improves productivity
- Built‑in tracing and token‑usage monitoring to optimize performance and cost in production
- Open‑source core for extensibility combined with scalable cloud‑native deployment options