TetraScience's Tetra OS platform addresses the core bottleneck in biopharma AI adoption: the lack of production-ready, AI-native scientific data. Built on Databricks and NVIDIA infrastructure, the platform comprises four layers: a Data Foundry that replatforms instrument data into AI-native schemas, a Use Case Factory delivering production-grade AI applications, an AI reasoning/orchestration layer, and Sciborg scientist-engineer hybrids. Concrete use cases include CRO Connect (80% reduction in preclinical data review time), AI-Augmented Biologics Discovery (94% binding prediction accuracy in 30 minutes vs. 48 hours), Lead Clone Selection Assistant (cell line development cut from 6-8 months to 2.5 months), and a Review-by-Exception Assistant that compresses batch release from weeks to days. The platform differentiates through productization, the Sciborg model bridging science and IT, and open data flows into Databricks Unity Catalog.
Table of contents
The Need for an OS for Scientific IntelligenceSolving the CRO Data Bottleneck: From Days to MinutesCutting Months from Antibody Development: From Iteration to PredictionSort: