Tempus AI (TEM) investor relations material

Company positioning and business model

• Identifies as a technology and AI company, not just diagnostics, with a dual focus on sequencing and data-driven insights.

• Generates proprietary data through sequencing and combines it with clinical data to create a unique, multimodal dataset.

• Balances two business lines: diagnostics (NGS) and data/AI, each appealing to different investor bases.

• Invests heavily in technology, with a large engineering team and significant cloud infrastructure.

• Strategic collaborations with major pharma companies, including recent multi-year, $100M+ deals.

Data acquisition, value, and competitive moat

• Requires hospitals to provide longitudinal clinical data in exchange for sequencing, building a rich, de-identified dataset.

• Data is harmonized, structured, and made accessible through proprietary tools, enabling deep cohort analysis.

• Dataset is difficult to replicate due to extensive hospital integrations and proprietary molecular data.

• Pharma clients value the unique combination of molecular and clinical data, leading to long-term, scalable partnerships.

• Anticipates increasing demand from large AI modelers as public data sources are exhausted by 2027–2028.

AI, foundation models, and future applications

• Building foundation models with partners (e.g., AstraZeneca) and independently, leveraging massive compute clusters.

• Models aim to deliver individualized predictions, such as drug response stratification in oncology.

• Envisions a new era of precision medicine, with AI-driven, N-of-1 contextualization for therapies.

• Regulatory environment in oncology allows flexibility for AI-driven insights, with more rigidity in other disease areas.

• Plans to expand datasets into new modalities (e.g., single-cell, spatial, proteomics) and disease areas.