Case Study: Recursion Pharmaceuticals achieves rapid, scalable discovery for 100 genetic diseases with Splunk Enterprise

Recursion Pharma Targets 100 Genetic Diseases With Splunk and Machine Learning

Recursion Pharmaceuticals, a Salt Lake City biotech startup aiming to discover treatments for 100 genetic diseases by 2025, faced a massive data and operational challenge: robotic microscopes and lab instruments generate terabytes of image and log data (about 700,000 TIFFs weekly), but the company lacked scalable logging, real-time visibility, and a way to unify diverse instrument data for fast decision-making across scientists, technicians and executives.

Recursion deployed Splunk Enterprise with DB Connect, the Machine Learning Toolkit and the Splunk Python SDK to centralize logs, enrich quality metrics and feed operational data into its proprietary ML pipelines. The platform delivered time to value in three days and full lab adoption in three months, provided real-time dashboards and anomaly detection across automated work cells, enabled hidden experimental insights, reduced reliance on costly LIMS software, and scaled to support the company’s high-throughput discovery workflow.

Recursion Pharmaceuticals

Ben Miller

Director of HTS Operations