Multi-agent systems require shared knowledge stores and coordination layers; Nemotron 3 Super's context length enables single agents to maintain conversation state, while Zilliz Cloud provides the persistent vector storage agents query and update.
Architects design specialized agents for different tasks—code generation, code review, testing, deployment—and they all access the same Zilliz Cloud deployment. Each agent retrieves relevant context, makes decisions, and contributes results back to Zilliz. The 1-million-token context window allows agents to review all prior decisions and context from other agents before acting, improving coherence.
Zilliz Cloud's managed nature eliminates infrastructure overhead: you define agent logic and let Zilliz handle vector storage scale, failover, and updates across your fleet. This is especially valuable for enterprises deploying agents across multiple teams or departments where a single shared vector store is necessary for coordination. Agents in financial services can share market intelligence, agents in customer service can learn from each other's interactions, and agents in software development can coordinate across codebases. How Zilliz ended up at the center of NVIDIA's unstructured data story at GTC 2026 discusses agentic patterns in modern AI.