Tempus AI unveils new generative AI tools for clinical care and research

Credit: Tempus AI

Tempus AI, Inc. on Tuesday announced new generative AI capabilities aiming to assist physicians and researchers in drawing insights from unstructured, multimodal healthcare data. The enhancements are designed to help clinicians make data-driven decisions for patient care while expediting research for new oncology treatments.

Tempus unveiled the new AI tools during the 2025 J.P. Morgan Healthcare Conference in San Francisco, according to media reports.

The company’s platform, Tempus One, launched in 2023 and taps into Tempus’ proprietary Large Language Model (LLM) Agent Infrastructure (Agent Builder) to analyze large volumes of clinical notes, imaging scans, and other unstructured records. According to the company, this approach can help health care providers piece together a more complete view of a patient’s medical history and speed up clinical trial enrollment, among other uses.

According to the news release, the new iteration of Tempus One includes four new breakthrough generative AI-powered capabilities that leverage LLMs to derive insights from unstructured data.

• Patient Query: Identifying and enrolling patients into clinical trials continues to be one of healthcare’s biggest challenges. Tempus offers a suite of tools that support providers and study sponsors to get the right patient on the right experimental treatment at the right time. As part of its clinical trial matching program, TIME, Tempus is now deploying an internal agent that allows the company to analyze providers’ structured and unstructured data to create a queue of patients that may be eligible for a specific trial. This agent can tap into unstructured data, such as progress notes, pathology reports, and imaging scans, which are important to understanding if a patient may be eligible for a trial. Tempus then sends the provider a notification for each patient that may be a match for that trial.
• Patient Timeline: Every patient’s journey is unique. Throughout their care, a cancer patient typically amasses hundreds of different records that document diagnostic results, treatment plans, physician notes, scans, and more. This makes it very difficult for physicians to have a comprehensive view of each patient’s journey. Tempus One offers a solution, which leverages generative AI to seamlessly weave together those documents and create a cohesive timeline for a specific patient. Using an LLM-based data science model, Tempus One turns digital health records into a structured timeline of clinical events, featuring diagnostic results, changes in treatment, and more. A separate agent is then applied to query structured data to answer explicit questions posed by a physician.
• Prior Authorization: Drafting and submitting prior authorization forms can require hours of administrative work for care teams, an arduous but necessary process to ensure that patients receive coverage for specific treatments throughout their care journey. Now, a new agent inside of Hub, Tempus’ provider platform, helps clinicians gather pertinent guidelines, drug labels, payer policy, and other relevant patient information, and outputs support documents tailored to each patient’s case for further use by their care team.
• Data Exploration: For the first time, researchers are able to ask questions and receive answers that are derived from both Tempus’ de-identified curated datasets and unstructured data housed within Lens, the company’s data analytics platform. Typically, real-world research has been hindered by manual chart reviews and data abstraction, but Tempus One can process millions of de-identified documents and provide initial answers in a fraction of the time. These datasets can include physician progress notes or medical images like pathology slides, providing researchers access to data that is not typically available, but critical when investigating new targets and patient populations. In particular, this new functionality expands the ability to investigate adverse events and reported symptoms, an increasingly popular query for many Tempus biopharma research customers.

“When we launched Tempus One a few years ago, our hope was that it would grow and scale in intelligence for the benefit of clinicians, researchers, and patients. We’ve been blown away by the evolution of this product which is designed to continually evolve so that we can easily deploy new generative AI solutions to our customers to address their evolving needs,” said Eric Lekfofsky, Founder and CEO of Tempus. “For example, LLMs now give us the opportunity to derive new insights from unstructured data, which has some of the richest patient data and until now, was extremely difficult to access at scale.”

Tempus, headquartered in Chicago, specializes in AI-enabled precision medicine solutions that aim to personalize patient care. Its multimodal data library and operating system are intended to provide physicians with tools that learn from each new piece of clinical information gathered.