Here are 1-3 brief analogies for Tempus AI (TEM):

1. Tempus AI is like the Tesla of precision medicine, leveraging AI and massive datasets to personalize diagnostics and guide treatment.

2. Think of Tempus AI as ChatGPT for medical data, using advanced AI to contextualize a patient's unique profile and generate personalized diagnostic insights and treatment paths.

• Intelligent Diagnostics: AI-enhanced laboratory tests that integrate a patient's clinical data to personalize results and guide therapy selection and treatment decisions across various disease areas.
• Clinical Next Generation Sequencing (NGS): Genomic sequencing services offered to patients, primarily in oncology, which are made more insightful by connecting results to a patient's personal clinical profile.
• Clinical Trial Matching Services: Services that leverage integrated multimodal patient data to identify and connect patients with relevant clinical trials.
• Data De-identification and Structuring Services: Services provided to healthcare institutions for processing, de-identifying, and structuring complex healthcare data.
• AI Applications (Analytical and Decision Support Capabilities): A product line offering advanced analytics and decision support tools, built upon their extensive data library, to aid physicians and researchers.

Tempus AI (TEM) primarily sells its products and services to other companies and healthcare professionals rather than directly to individuals. Its major customers fall into the following categories:

1. Pharmaceutical Companies: Tempus AI's offerings have been used by approximately 95% of the largest public pharmaceutical companies (based on 2023 revenue). These companies leverage Tempus AI's data, analytics, and intelligent diagnostics to support drug discovery, development, and therapeutic applications. Specific company names are not provided in the description.

2. Healthcare Institutions: This category includes hundreds of provider networks and more than 65% of all academic medical centers in the United States. These institutions order Tempus AI's diagnostic products and services (such as Next Generation Sequencing, or NGS), utilize its platform for clinical decision support, and engage in services like clinical trial matching.

3. Physicians and Researchers: These professionals, often operating within the aforementioned healthcare institutions and pharmaceutical companies, are direct users and beneficiaries of Tempus AI's intelligent diagnostics and AI applications. They use the platform to make personalized, data-driven decisions to improve patient care and accelerate drug discovery and development.

Eric Lefkofsky, Founder & Chief Executive Officer

Eric Lefkofsky is the Founder and CEO of Tempus AI. A serial entrepreneur, he co-founded several successful companies before Tempus, including Groupon, Mediaocean, Echo Global Logistics, and InnerWorkings. He also serves as a co-managing partner of Lightbank, a venture capital firm. Lefkofsky founded Tempus AI in 2015, driven by a personal mission to improve patient outcomes through data-driven solutions, after his wife's breast cancer diagnosis.

James Rogers, Chief Financial Officer

James Rogers has served as Tempus AI's Chief Financial Officer since April 2021. He joined Tempus in 2017 as the first finance hire, building the finance function and helping guide the company through its public offering. Prior to Tempus, he held various finance positions at Groupon, including leading Financial Planning & Analysis (FP&A) for the North America business and serving as the financial controller of Asia Pacific operations. Rogers began his career in audit at Ernst & Young.

Ryan Fukushima, Chief Operating Officer

Ryan Fukushima has been the Chief Operating Officer at Tempus AI since September 2015 and was part of the founding team. He is also a co-founder and currently serves as CEO and a director of Pathos AI, Inc. Before joining Tempus, Fukushima was an Entrepreneur-in-Residence and Vice President at Lightbank LLC, a venture fund. He also worked at Hyde Park Venture Partners and as an engineer for Cisco and VMware.

Shane Colley, Chief Technology Officer

Shane Colley is the Chief Technology Officer at Tempus AI. Before joining Tempus, Colley was the Vice President of Research and Development at R1 RCM (formerly Accretive Health), where he was responsible for building and leading a global organization of over 200 professionals focused on R1's technology portfolio.

Ezra Cohen, MD, Chief Medical Officer of Oncology

Dr. Ezra Cohen joined Tempus AI in May 2023 as the Chief Medical Officer of Oncology. He is a prominent medical oncologist and cancer researcher with extensive clinical and research experience. Prior to his role at Tempus, Dr. Cohen served as the Chief of the Division of Hematology-Oncology and the Associate Director of Clinical Science at UC San Diego (UCSD) Moores Cancer Center. He also spent 15 years at the University of Chicago, where he co-directed the Head and Neck Cancer Program.

Key Risks to Tempus AI (TEM)

• Regulatory and Data Privacy Compliance: Tempus AI operates in a highly regulated healthcare environment, necessitating strict adherence to data privacy laws such as HIPAA in the United States. The company's business model relies heavily on acquiring and processing sensitive patient data, both as a covered entity and a business associate. Non-compliance, data breaches, or evolving regulatory landscapes (including those specific to AI in healthcare) could lead to significant legal penalties, reputational damage, and operational restrictions on their ability to collect and utilize data.
• Dependence on Data Acquisition and Healthcare Institution Partnerships: Tempus AI's core "Intelligent Diagnostics" and AI models are built upon one of the largest libraries of clinical and molecular oncology data, amassed through approximately 450 unique data connections with over 2,000 healthcare institutions. The company's continued success is fundamentally reliant on establishing and maintaining these data pipelines and strategic partnerships. Any disruption to these critical relationships, challenges in securing new data agreements, or increased costs associated with data acquisition and integration could severely impair its ability to grow its proprietary dataset, develop and train its generative AI models, and deliver its products and services.
• Efficacy, Clinical Adoption, and Competition in AI-Powered Diagnostics: The company's value proposition centers on leveraging AI, including generative AI, to create more accurate and personalized diagnostic tests. There is an inherent risk that the AI models may not consistently achieve the anticipated accuracy or clinical utility, or that they may face challenges in widespread adoption by physicians and healthcare systems. Furthermore, the market for AI in healthcare and diagnostics is becoming increasingly competitive, with both established corporations and agile startups vying for market share. Tempus AI must continuously innovate and demonstrate tangible benefits to distinguish its offerings and secure market penetration amidst this competitive pressure.

Expected Drivers of Future Revenue Growth for Tempus AI (TEM)

Tempus AI (TEM) is expected to drive future revenue growth over the next 2-3 years through several key initiatives, focusing on its core diagnostics business, advanced AI capabilities, and strategic market expansion:

1. Growth in Diagnostics Volume, particularly in Oncology and Hereditary Testing: Tempus AI anticipates continued strong growth in the volume of its diagnostic tests, especially within oncology and hereditary testing. The company reported a 29% increase in oncology unit volume and a 23% increase in hereditary testing in Q4 2025, with similar momentum expected to continue. This growth is supported by increasing adoption of genomic sequencing in cancer care and the expansion of Tempus's comprehensive test portfolio.
2. Increased Average Selling Prices (ASPs) and Improved Reimbursement: A significant driver of revenue growth is the projected increase in average selling prices (ASPs) for Tempus's diagnostic tests. Management expects substantial ASP upside, with an outline of more than $500 per test of potential ASP improvement over time. This improvement is largely attributed to the transition of volume from lab-developed tests to FDA-approved versions, such as the xT CDx, which is priced at $4,500 compared to the previous $1,630-$2,200 range for its primary oncology test. Additionally, the company anticipates that continued FDA approvals and the shift of tests into Advanced Diagnostic Laboratory Test (ADLT) status will help improve reimbursement rates.
3. Expansion and Monetization of Data and AI Capabilities: The "Data and Services" or "Insights" segment is a rapidly scaling, high-margin revenue stream for Tempus AI. This segment, which includes data licensing and AI algorithm commercialization, delivered 69% reported revenue growth in Q4 2025 (including a one-time warrant impact) and is projected to grow by roughly 40% in the following quarter. Tempus has a strong commercial pipeline, with total contract value exceeding $1.1 billion, providing significant visibility into future data-driven expansion. Strategic collaborations, such as multi-year agreements to build multimodal foundation models in oncology, are also contributing to this segment's growth.
4. Launch of New Diagnostic Products and Expansion into New Disease Areas: While oncology remains a primary focus, Tempus AI is expanding its diagnostic offerings and entering new disease areas. The company has launched new liquid biopsy assays like xM for Treatment Response Monitoring ("TRM") and expects the xF liquid biopsy FDA submission to have a significant impact on revenue starting in 2027. The background also mentions expansion into neuropsychiatry, radiology, and cardiology, indicating a broader market reach for its Intelligent Diagnostics.

Capital Expenditures

• Capital expenditures have primarily focused on the development and expansion of the Tempus Platform, which includes proprietary software and the establishment of a network of approximately 450 unique data connections across more than 2,000 healthcare institutions.
• Significant investment has been directed towards building and maintaining a unified multimodal database and cloud infrastructure, which now houses over 200 petabytes of data, serving as a proprietary training dataset for generative AI applications.
• The company has also focused capital on expanding its Intelligent Diagnostics and AI applications beyond oncology into new disease areas such as neuropsychiatry, radiology, and cardiology, by leveraging large amounts of de-identified data.