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Data Connectors

For AI agents to function effectively within the platform, they need secure access to diverse sources of enterprise data. This is achieved through connectors and API endpoints that link internal systems like customer relationship management, enterprise reporting platforms and point of sale systems. The data ingestion/retrieval system ensures security, scalability, and reliability. Ingested data is transformed into embeddings and stored in a vector database for efficient semantic searches in RAG workflows. Emerging standards, such as Model Context Protocol (MCP), aim to provide structured ways for AI agents to discover and interact with external data sources and tools. Toolkits like NVIDIA’s open-source NeMo Agent Toolkit help developers build, connect and optimize the AI agents using retrieved enterprise data for complex reasoning, planning, and multi-step task execution.