Morgan Stanley Technology, Media & Telecom Conference 2026
Logotype for Tempus AI Inc

Tempus AI (TEM) Morgan Stanley Technology, Media & Telecom Conference 2026 summary

Event summary combining transcript, slides, and related documents.

Logotype for Tempus AI Inc

Morgan Stanley Technology, Media & Telecom Conference 2026 summary

3 Mar, 2026

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.

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