Tempus AI

Tempus reports connections to roughly 65% of U.S. academic medical centers and 55% of U.S. oncologists, more than 45M research records, 45K+ patients identified for potential clinical-trial matching and 500+ petabytes of multimodal healthcare data.

Tempus reported $382.5M Q2 2026 revenue, 31% year-over-year oncology volume growth, 9,000 MRD tests in the quarter and about $200M in new Data and Applications licenses.

Tempus reported $382.5M Q2 2026 revenue, 31% year-over-year oncology volume growth, 9,000 MRD tests in the quarter and about $200M in new Data and Applications licenses.

Tempus develops multimodal foundation models and agentic clinical workflows using more than 500 petabytes of data, 45M+ de-identified patient journeys and molecular, imaging and clinical data.

Tempus develops multimodal foundation models and agentic clinical workflows using more than 500 petabytes of data, 45M+ de-identified patient journeys and molecular, imaging and clinical data.

Tempus is developing multimodal biological foundation models and agentic workflows on 500+ petabytes of molecularly grounded data; its latest transformer-based oncology model was trained on 2.5M longitudinal records, 250M+ pages of clinical notes, 450K medical images and 500K genomic/transcriptomic sequences.

Tempus combines diagnostics, FDA-approved companion diagnostics, data licensing, pharma partnerships and health-system collaborations including USC, BMS, Merck, Gilead and others.

Tempus combines diagnostics, FDA-approved companion diagnostics, data licensing, pharma partnerships and health-system collaborations including USC, BMS, Merck, Gilead and others.

Tempus ended 2025 with more than $1.1B in total remaining contract value and 126% net revenue retention; its data agreements span more than 70 customers including major global pharma companies, supporting durable healthcare-AI commercial scale.

Tempus introduced Workspaces within its Lens analytics platform, providing virtual-machine research environments supporting Python and R, data querying and analysis templates. These concrete analytics and research-software workflows support an inference of transferable data-science skills alongside the existing healthcare-modeling evidence.

ML, multimodal data, genomics, diagnostics and clinical AI skills transfer strongly within health-tech and biotech, but regulated healthcare specialization constrains full market portability.

ML, multimodal data, genomics, diagnostics and clinical AI skills transfer strongly within health-tech and biotech, but regulated healthcare specialization constrains full market portability.