Enterprises are rapidly moving from isolated copilots toward ecosystems of specialized AI agents that collaborate across business processes, data domains, applications, and cloud platforms. Multi-agent systems can improve decomposition, parallel execution, specialization, resilience, and decision quality, but they also introduce architectural challenges involving identity, delegation, shared memory, tool access, message routing, conflict resolution, security, observability, and accountability. This paper proposes an Enterprise Multi-Agent Architecture Framework that defines a layered architecture for agent discovery, orchestration, inter-agent communication, knowledge grounding, enterprise integration, policy enforcement, runtime isolation, and human oversight. The framework combines enterprise architecture principles, Zero Trust, Responsible AI, Retrieval-Augmented Generation, Knowledge Graphs, API governance, event-driven integration, and lifecycle management. It enables organizations to design scalable multi-agent environments in which specialized agents can collaborate safely while maintaining traceability, bounded authority, data protection, and measurable business outcomes across hybrid and multi-cloud landscapes.

Sanjeeve Kumar Gajadi, "Enterprise Multi-Agent Architecture Framework" International Journal of Scientific Research and Engineering Development, V9(5): Page(666-669) September - October 2026. ISSN: 2581-7175. www.ijsred.com. Published by Scientific and Academic Research Publishing.