
Experiment tracker purpose-built for foundation models
Neptune.ai provides a specialized experiment tracking solution designed specifically for the demands of foundation model training at scale. The platform differentiates itself through its ability to handle massive metric volumes without performance degradation, making it particularly suited for organizations training large language models. The pending acquisition by OpenAI serves as significant third-party validation of the platform's capabilities.

Neptune.ai is an experiment tracking platform purpose-built for foundation model training, enabling AI research teams to monitor and debug large-scale model training at GPT-scale and beyond. The platform allows users to log and visualize thousands of per-layer metrics—including losses, gradients, and activations—without the performance tradeoffs typically associated with tracking at such scale. With capabilities designed to handle models ranging from 5B to 150T parameters, Neptune.ai provides real-time visualization with no lag, accurate chart rendering, and deep debugging tools to identify issues like vanishing gradients, batch divergence, and loss convergence failures. Founded to address the unique challenges of training foundation models, Neptune.ai has gained significant traction among AI researchers and enterprises, with over 60,000 researchers using the platform. The company offers both cloud-hosted and self-hosted deployment options, with enterprise-grade security features including SOC2 Type 2 compliance, GDPR compliance, RBAC, and SSO authentication. In a notable validation of its technology, Neptune.ai has entered into a definitive agreement to be acquired by OpenAI, the organization behind GPT models, which itself uses Neptune for monitoring and debugging its training processes.