Company: TEM
Filing Date: 2025-02-24
Form Type: 10-K
Source: 0000950170-25-025603
Chunk: 11

Company: Tempus AI, Inc.
Filing Date: 2025-02-24
Form: 10-K
Item: Item 1
Chunk 11
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 raw files associated with the testing we perform) we serve, those clinicians can use the data to further their own research efforts to help patients.

Our Proprietary Multimodal Database

We believe most healthcare databases lack real-time functionality, depth among data types, and the scale of matched clinical and molecular records needed to meaningfully improve therapeutic research and development. Tempus is attempting to solve this problem by democratizing the use of near-real time molecular, clinical, and imaging data by embedding our solution into the clinical care of patients. As our testing volume has grown, and as our dedicated data pipelines have expanded, the size of our database has increased exponentially. Since we launched our Platform in 2016, Tempus has amassed over 900 million documents, across more than 7.3 million de-identified patient records, including over 1.1 billion pages of rich clinical text that we use to train our large language models. The database also includes over 1,400,000 records with imaging data, more than 1,300,000 with matched clinical records linked with genomic information, and more than 260,000 with full transcriptomic profiles. Within oncology specifically, we believe this represents one of the largest and most comprehensive molecular libraries of cancer patients in the world. The breadth of our database, the quality and diversity of our data, as well as its regularly updating nature, allow us to offer a variety of AI-enabled solutions to the market. We believe our unique data set enables us to bring the benefits of generative AI and large language models to healthcare, as our curated, multimodal database can be used as a proprietary training set to build a variety of AI based applications, which we intend to deploy through our existing network and distribution platform. We also retain the rights to broadly commercialize de-identified data. As the amount of data in our cloud environment continues to grow from its current size of more than 240 petabytes, we believe new AI applications and opportunities will emerge that are only possible with scale, driving innovations in patient treatment that were previously unattainable. The following diagram represents the growth of our database over time.

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Another valuable attribute of our dataset is the number of different data modalities represented. We believe multimodal data is a necessary predicate to successfully build and deploy AI-based applications given the complexity of disease and the various attributes across different forms of data (e.g., text, images, molecules, etc.). As of December 31, 2024, our database included the following types of data