openJiuwen Releases Enterprise-Grade Distributed Swarm Architecture, Deployed by Postal Savings Bank

openJiuwen believes that enterprise Agent scaling must overcome four barriers: scale, cost, management, and security. Single-machine compute limits the number of agents and concurrent tasks; deploying separate instances per user or business is costly and leaves resources idle; scattered instances form silos, making unified governance difficult; and highly regulated industries demand strict identity authentication, data isolation, and behavior traceability. These four factors are interdependent and require engineering trade-offs.

openJiuwen's enterprise-grade distributed swarm architecture is not simply about moving to the cloud; it builds a complete distributed swarm networking system, divided into access layer, framework layer, distributed runtime layer, and system service layer. The platform uses enterprise cluster resources as a base to uniformly support agent access, operation, collaboration, governance, and security, while maintaining boundaries between tenants, users, and instances.

The architecture includes built-in compute affinity, aligning with Ascend and Kunpeng compute infrastructure, supporting proactive affinity for context and KV Cache to mitigate long-running cache invalidation, and unifying scheduling of general and intelligent compute resources to reduce latency, increase throughput, and save tokens. In deployment, users connect via the JiuwenSwarm Gateway, integrating with existing enterprise identity systems; agent instances are deployed as either personal dedicated single containers or shared container clusters for departments, with skills and tools executed in isolated sandboxes.

Postal Savings Bank of China has built a financial swarm intelligence platform based on this architecture and deployed it in production, marking the first successful enterprise production deployment of the distributed swarm architecture. The platform integrates with the bank's existing SSO, self-built SkillHub, and legacy business systems without altering the original systems or permission boundaries.

The platform addresses three requirements of financial production environments: handling high concurrency through resource sharing and on-demand elastic scheduling; implementing unified admission and authorization for tools and skills, executing them in isolated environments, and providing full-chain observation and auditing; and supporting unified skill listing/delisting, dynamic user and group configuration, and centralized agent configuration distribution. Currently, Postal Savings Bank has fully deployed the platform in production, focusing on smart office, intelligence monitoring, and risk early warning scenarios.

openJiuwen believes that enterprise-level competition for Agents has moved beyond the demo stage, and the real test is whether the underlying platform can overcome the four barriers of scale, cost, management, and security. Its answer is an enterprise-grade swarm architecture centered on high scalability, low cost, strong governance, and high security. The production deployment at Postal Savings Bank provides a replicable engineering practice sample, pointing toward AI Agents becoming a new form of productivity that sustainably creates business value.