How FactSet cut model training and deployment from days to hours with Databricks AI Runtime

FactSet cut the time to set up, train and deploy its custom Text-to-Formula model from days to hours by running fine-tuning on Databricks AI Runtime's serverless GPU infrastructure.

The company retrains its models roughly every two to three weeks and has worked with Llama-based models while evaluating newer open models. Training runs inside its existing Lakehouse workflow, with MLflow tracking experiments and governed data.