Financial ServicesGenerative AIRetrieval-Augmented GenerationAI Model Development & MLOpsCode Generation
FactSet cuts code-generation response time 70% with a standardized Databricks LLMOps framework
FactSet, a financial data and analytics provider, standardized its GenAI development on Databricks Mosaic AI and managed MLflow after fragmented tooling across teams caused collaboration and governance problems. For its FactSet Mercury code-generation feature, FactSet fine-tuned meta-llama-3-70b and Databricks DBRX models, reducing average response latency by more than 70%. Its Text-to-Formula project reduced end-to-end latency by about 60% using a compound AI architecture with fine-tuned open-source models.
FactSet
Databricks Mosaic AI · Databricks-managed MLflow · Unity Catalog +3
