Case Study: Evariant achieves 10x faster predictive modeling with DataRobot

Speeding Up the Predictive Analytics Process with Automated Machine Learning

Evariant, a fast-growing SaaS provider of CRM solutions for healthcare, faced a bottleneck in delivering predictive analytics: complex clinical and marketing data limited their team to only a few models per month, and the hands-on data preparation made scaling impractical. To overcome this, Evariant turned to DataRobot’s automated machine learning platform (hosted on AWS) to enable faster, more reliable model building and deployment.

DataRobot automated and semi-automated model building, validation, and scoring using a collaborative cross‑validation framework, allowing Evariant to produce thousands of validated models and increase model output to nearly 10x its previous pace. The DataRobot platform saved time and headcount (avoiding roughly two full‑time hires), improved the quality of cross‑sell/up‑sell/retention and acquisition strategies, and drove higher ROI for both Evariant and its healthcare clients.

Evariant