Understand the AI Factory Architecture# Agent Factory Architecture on Hybrid Manager Architectural Overview Core Components Model Library Inference Server Infrastructure Langflow Runtime Storage Infrastructure Use Cases and Personas for Agent Factory on Hybrid Manager Overview Key Use Cases Internal Knowledge Management Customer Service Automation Enterprise RAG Systems AI-Enabled APIs User Personas Platform Engineers Data Scientists Application Developers Business Analysts Industry-Specific Implementations Financial Services Healthcare Manufacturing Implementation Considerations Scalability Planning Security Requirements Performance Optimization Getting Started by Use Case For Knowledge Management For Customer Service For API Development Additional Resources Frequently Asked Questions - Agent Factory on Hybrid Manager Table of Contents Platform Capabilities What types of models does Hybrid Manager support? Can I deploy custom models? What distinguishes Agent Factory from cloud AI services? Installation and Setup What are the minimum infrastructure requirements? How do I configure GPU nodes for NIM models? Can Agent Factory operate in air-gapped environments? Model Management How do I deploy NVIDIA NIM models? Which NVIDIA NIM models are available by default? How do I manage NIM model versions? Langflow Operations and Maintenance How do I monitor NIM model performance? How should I handle NIM model updates? Troubleshooting NIM model fails to start - diagnostic steps? High inference latency - optimization strategies? Poor retrieval quality in RAG applications? Security and Compliance How do I implement access control? What encryption is implemented? Which operations are audited? Performance and Scaling How do I configure resource quotas? When should I scale horizontally versus vertically? What model sizes can Hybrid Manager support? Additional Resources
