Understand
Define the application, model, data boundaries, and success criteria.
Start with a measurable task. We assess baseline models, retrieval approaches, and fine-tuning options before defining a development engagement.

Teams with a defined task, representative data, and a clear way to measure quality.
Training feasibility, data preparation, model licensing, and ownership are assessed for each engagement. Training a large model from scratch requires a separate feasibility assessment.
Define the application, model, data boundaries, and success criteria.
Assess the workload, compute needs, deployment design, and support scope.
Validate the environment and model against agreed acceptance criteria.
Agree monitoring, maintenance, ownership, and change procedures.