Automate and optimize the configuration of radio access network (RAN) parameters using agentic AI and a large language model (LLM)-driven framework.
Continuously extract, embed, and index multimodal data for fast, accurate semantic search. Built on world-class NeMo Retriever models, the RAG blueprint connects AI applications to multimodal enterprise data wherever it resides.
Optimized SLM for on-device inference and fine-tuned for roleplay, RAG and function calling
A general-purpose LLM with state-of-the-art performance in language understanding, coding, and RAG.