The product provides a shared workspace for customer-specific model adaptation: dataset intake, fine-tuning job orchestration, evaluation tracking, deployment readiness checks, and feedback-to-model-change traceability. It integrates with existing model stacks and pipelines so research, MLE, product, and forward deployed teams can manage each customer model variant without stitching together internal tooling.

Open-weight and enterprise-customized models are pushing AI companies to operationalize fine-tuning, inference, and evals for many customers at once. Hiring signals from model labs and AI infrastructure teams indicate this workflow is becoming a core production bottleneck.