Data for Agents

Building effective AI agents is a data problem that extends beyond model weights to include software traces, tool-use failures, and multi-step reasoning. NVIDIA's Nemotron open data products, such as Nemotron-CC, use synthetic data to enhance datasets for pretraining and improve reasoning capabilities. Synthetic data allows organizations to contribute valuable data signals to the community without exposing proprietary secrets, fostering a more diverse AI ecosystem. To make this data accessible, tools like the Nemotron Post-Training v3 Prompt Atlas offer visual exploration, while Nemotron-Personas help create locally grounded synthetic profiles for better agent understanding.