Tempus AI Hits $1.1B TCV, Posts First Positive EBITDA and Debuts Paige Predict

TEMTEM

Tempus AI reached $1.1B total contract value with 70+ pharma data deals and posted its first positive adjusted EBITDA in Q3 2025. It launched Paige Predict, an AI-powered pathology suite predicting 123 biomarkers across 16 cancer types from H&E slides using a model trained on 200K patient records.

1. Record Third-Quarter Profitability

Tempus AI reported its first positive adjusted EBITDA in Q3 2025, marking a pivotal shift toward sustainable profitability. The company achieved positive adjusted EBITDA driven by a 35% year-over-year increase in service revenues from its genomic sequencing and AI-driven diagnostic solutions. Operating expenses remained flat compared to Q2, reflecting improved operational efficiency and disciplined cost management. Management indicated that this profitability milestone will support reinvestment in research and development without reliance on external financing.

2. Expansion of Pharma Partnerships and $1.1 B Total Contracted Value

During the first nine months of 2025, Tempus secured over 70 new data-licensing and co-development agreements with leading pharmaceutical firms, bringing its total contract value (TCV) to $1.1 billion. These partnerships span oncology, immunology and rare diseases, with an average contract term of four years and expected annual recurring revenue growth of 25%. The depth and diversity of these agreements reinforce Tempus’s position as a preferred provider of AI-powered clinical and molecular insights for drug discovery and development.

3. Launch of Paige Predict Strengthens Digital Pathology Offerings

Tempus introduced Paige Predict, an AI suite capable of analyzing H&E whole-slide images to forecast the presence or absence of 123 biomarkers across 16 cancer types. Built on a combined dataset of over 200,000 de-identified patient records, the model demonstrated over 92% accuracy in retrospective validation studies. This launch addresses the ‘quantity not sufficient’ challenge in tissue samples by guiding clinicians on optimal testing sequences, potentially reducing repeat biopsies by up to 40% and accelerating time to actionable insights for personalized treatment decisions.

Sources

BZ