GAN | Venus Citizen

Entrepreneur, husband, father and Die-Hard Flower Girl NFT Collector

[Audit The Herd @AuditTheHerd]

People will only start to look into $TEM when it’s above $100. My favorite part of investing is trying to see what others can’t.

I don’t know when the aha moment happens but it feels close.

[J Keynes @JKeynesAlpha]

$TEM 👀 market waking up! 🔥 🔥 🔥 more than just the $PLTR of healthcare!

[J Keynes @JKeynesAlpha]

$TEM $PLTR Why "The Palantir of Healthcare" Undersells Tempus: A Colossus in the Making

The "Palantir of healthcare" tag is a fair starting point and a ceiling the business has already cleared. Palantir built the integration and ontology layer for enterprise and government data, then deployed it as the decision system on top of information its customers already owned. Tempus does that inside healthcare and adds three layers Palantir does not have: 1) It manufactures the underlying data, 2) it owns the distribution rails that carry the insight back to the decision-maker, and 3) it runs frontier-scale compute to model the data itself. The honest description is that Tempus AI is a health care COLOSSUS in the making that fuses a data factory, a cloud provider, a foundation-model lab, and a clinical distribution network into one company.

The doctrine Lefkofsky constantly articulates is the spine. Durable AI businesses require two things, "vast amounts of proprietary data to build models" and "a distribution system to take those insights and deliver them to the hands of physicians and patients." His summary: "Tempus is unique in that it has both." He sharpens it into a warning that the model builders "all become largely commoditized within 6 to 12 months," while value accrues to whoever owns the data and "the distribution of the insight back to the client." Palantir lives on the distribution and integration half. Tempus owns both halves and the factory feeding them.

The factory is what the comparison misses. The data set runs more than 500 petabytes across over 45 million patients, with more than 9 million images, over 4.5 million sequenced samples, and more than 400,000 deep multimodal records that combine DNA, RNA, imaging, clinical notes, outcomes, and adverse-event data on the same patient. The footprint underneath is roughly 5,500 connected institutions and about two-thirds of all US academic medical centers, and Tempus is the largest sequencer across the National Cancer Institute (NCI) designated centers.

When the American Society of Clinical Oncology (ASCO) chose a partner to abstract cancer data at scale, Tempus was one of two. The generation rate is simply an astonishing number. Eli Lilly was touting 700 terabytes of data "collected over the past century," and Lefkovsky's retort was "I think we generate 700 terabytes of data every 12 hours." Tempus adds 20 to 30 petabytes a month and purges data because the storage cost is too extreme to keep all of it. Palantir does not generate proprietary data of this kind. It organizes what a client brings.

The distribution moat is the harder one to copy. Building it is "like mowing 3,000 lawns," the years of legal work, business associate agreements, and information-technology integration sitting behind thousands of hospital connections, and "the people that want to do what we do will have to in some way, shape or form, build all those connections." The stack riding those rails is its own fortress, and it helps to define the pieces.

Epic is the electronic health record (EHR) system most large US hospitals run on, the system of record for a patient's chart. Edge is the Tempus server that reaches past the EHR to pull in data the chart never holds: computed tomography scans and other medical imaging files (DICOM), digitized pathology slides, and the separate wave files a 12-lead electrocardiogram (ECG) produces. Edge structures all of it. Air is the platform that pushes the finished insight back to the physician inside Epic or whatever EHR they run. Locker is the security and protection layer that lets a provider open its data to Tempus "without it losing security and protection of that data." The relationship this produces becomes a triad, "patient to technology to physician," and the design goal is to "make good doctors great doctors, and great doctors superhuman."

This is the architecture behind one of his most aggressive claims, that the frontier model labs $GOOG, Anthropic, OpenAI, $SPCX via xAI, do not threaten Tempus and resolve into its customers. The general-purpose systems "were not trained on health care data, they were trained on Internet data," so they cannot natively handle raw sequencing files (BAM) or DICOM imaging.

Lefkovsky's conclusion: "even if big pharma wanted to build these models, or the big foundation model people wanted to build these models, they're going to have to come to somebody like Tempus that has this kind of unrestricted data."

The compute underwriting it is the part that should stop a skeptic. Tempus's capacity is "probably equal to all of pharma combined," including a GB200 cluster roughly four times the size of the 1,008 H200s running the foundation model built with AstraZeneca and Pathos, a model Tempus funded with about $200 million while $AZN AstraZeneca provided the majority. That model already cleared AstraZeneca's bar, hitting a survival-prediction benchmark (the C-index, a concordance metric) on both a public trial and a private trial that AstraZeneca's own tuned internal model had been trained on. The validation arrived without prompting when the chief executives of Merck and AstraZeneca each named Tempus as strategic to their AI initiatives within ten days, "one in an earnings report and one on CNBC," which "doesn't happen" in big pharma.

The customer roster reads like the field. Tempus works with 19 of the 20 largest pharmaceutical companies and more than 250 biotechs. AstraZeneca signed the first strategic partnership in 2021 and now funds the foundation model. $GSK came on as another large partner, $MRK Merck signed strategically and "is just starting to grow and prosper in every which direction," and expanded collaborations with Merck, Gilead, and Bristol Myers Squibb were announced over recent months. On the deployment side, Northwestern is the reference account, where Tempus spent years "building pipes" and now runs its ECG platform at scale (not to mention USC, Yale, and many other prestigious medical centers).

Demand has inverted the usual sales motion. The just-in-time trial network "has too many people that want in," with a waiting list, to the point where Tempus tells pharma "it's too many" and turns trials away. His framing of why pharma cannot opt out: "I can't be blindsided when I have a $1 billion franchise or a $5 billion franchise that unravels on me at the last minute." The summary line on the moat is the one to sit with: "Our data business is big and growing, and we have almost no competition," echoed by his data chief, "we don't see any competitors in our space."

The endgame is where the bull case gets even more bullish. "There will come a time when no Phase IIIs ever fail, and some company like Tempus will be responsible for that." The logic is that a large trial fails for one of two reasons, a misunderstood mechanism or a Phase II signal that does not reproduce, and real-world data at scale addresses both. Customers have already measured returns on investment in the 30 to 50 times range on single immunotherapy projects and net present values north of $500 million on individual go or no-go decisions.

The platform increasingly sells models rather than raw files, to the point where "it's rare that people just want our data," and one live deal involves "just licensing embeddings" with no files moving at all. On the diagnostic side his conviction is total: "I'm 100% convinced that old world of targeted therapy will die and this new world of precision medicine will show up." The algorithmic layer he expects to become "probably the largest of all of our businesses by far," where a single ECG algorithm could become a one-billion to two-billion-dollar product, and where "even if you spend $1 billion generating an algorithmic insight, you're likely going to save the U.S. health care system $50 billion or $100 billion of mistake."

The financials confirm the compounding. More than $2 billion in data licensing signed, 126% net revenue retention for 2025, more than $1.1 billion in total contract value, and roughly $87 million in data revenue last quarter growing faster than the company average. The customer base widened from 35 companies in 2020 to about 240 in 2025, and top-five concentration fell from 85% to 59%. The tumor-only FDA approval announced the morning of Investor Day brought essentially the entire DNA portfolio under Advanced Diagnostic Laboratory Test pricing, an estimated $75 million to $100 million of revenue at little incremental cost.

The clearest read on the embedded value is how Lefkofsky talks about it. "If we took our data business public under normal terms, it would probably be worth significantly more than Tempus in totality," and possibly at twice that, which implies the diagnostics business is being assigned close to negative value inside the current price. He blames an investor base where "the diagnostic investors hate the technology and data business they don't understand and the technology investors hate the diagnostic business." His starkest measure of the asset is the trade he says he could make today: walk into any sub-billion-dollar oncology biotech, offer data access for 20% of the company, and "almost every one of them would be like great."

Put it together. Tempus generates the molecular substrate of disease at petabytes a month, harmonizes it into the deepest multimodal records in the field, models it on compute rivaling all of pharma, and ships the answer back through rails into 5,500 hospitals that took a decade to lay. It is going after the largest pool in a $6 trillion system, which he identifies as "error and waste." Palantir built one layer of that stack brilliantly. Tempus is building the entire stack, and the layers it owns that Palantir never will are the data factory, the distribution network, and the compute. That is what a company outgrowing its own comparison looks like.

The deeper point is that the Palantir comparison does not go far enough. Palantir is a reference for how powerful a data and software moat can become inside a single company. Tempus is building something the market does not yet have a category for, the core infrastructure layer of precision medicine, generating the data, modeling it on frontier compute, and distributing the answer across the entire clinical and pharmaceutical system at once. Companies that define a new category and own its foundational asset do not stay mid-cap. They become titans. I expect Tempus to grow into a megacap in healthcare, and I expect the rerate to be dramatic once the market resolves the two-business confusion and prices the data engine for what it is. We are still in the first inning of the ball game. Re-ratings of that kind reward the investors who sized early and waited, and they tend to arrive faster and steeper than the models call for. That asymmetry is the reason Tempus is one of the largest and still increasing positions in my portfolio.

(This analysis is drawn from Eric Lefkofsky across three recent appearances: the May 29 Investor Day, the June 8 Goldman Sachs healthcare conference, and the February 23 Heart of Healthcare podcast. The quotes are his.)

[Massimo @Rainmaker1973]

Atlas from Boston Dynamics showing advanced agility with a cartwheel followed by a clean backflip. This is insane.

[Tempus @TempusAI]

That’s a wrap on #Elevate26: our Global Sales Meeting 🚀 Four days of impactful collaboration, educational sessions, and meaningful reflection on how we’re advancing precision medicine, strengthening partnerships, and driving real-world impact.

[Weary Centurion @weary_centurion]

$TEM

“A future where people live longer and healthier lives; a future where
words like cancer and diabetes feel like ancient Latin terms. I believe we are closer to this future than most people realize, and we will do everything in our power to expedite its arrival.”

[J Keynes @JKeynesAlpha]

$TEM We are still at the very beginning of what AI can do with Tempus’ massive proprietary dataset. The scale of this data and the models being built on top of it are going to unlock entirely new capabilities in precision medicine and materially improve patient outcomes. This story is just getting started.

[Tempus @TempusAI]

Today is #WorldCancerDay. It's fitting that right now, more than 600 Tempus team members are gathered in Chicago for our Global Sales Meeting.

We had the privilege of hosting Romy Leroy for a "Patient Perspective" session, hosted by Dr. Gary Grad. Romy was diagnosed with stage 4, triple-negative breast cancer and after receiving her test results from Tempus, was put on a immunotherapy/chemo combination treatment. She now has no evidence of disease.

Romy’s story is a living reminder of our 'why.' On #WorldCancerDay and every day, the Tempus team is dedicated to helping make sure patients are on the right drug at the right time, so they can live longer and healthier lives.

[GAN | Venus Citizen @NftGly]

@jye1968 @xuejianosaka 红车司机没有足够提前减速刹车，所以撞人红车责任较大. 白车追尾责任是肯定的， 但撞人这件事白车不该追责

[GAN | Venus Citizen @NftGly]

@__Inty__ @grok 分析一下

[GAN | Venus Citizen @NftGly]

@CroAglo @TheInsiderPaper @grok @grok, what substance might be found in sewers that can burn green?

[Peter Beck @Peter_J_Beck]

Perfect transfer orbit,

[Peter Beck @Peter_J_Beck]

100% mission success!

[GAN | Venus Citizen @NftGly]

@RocketLab @BlackSky_Inc Congrats！

[Rocket Lab @RocketLab]

PAYLOAD DEPLOYMENT CONFIRMED! That’s mission success for Electron’s 60th launch 🚀 Welcome to space, @blacksky_inc

[GAN | Venus Citizen @NftGly]

@RocketLab Congrats！

[Rocket Lab @RocketLab]

We're live with today's launch coverage for 'Fasten Your Space Belts', our 60th Electron mission. https://t.co/nTnd7ZwYMI

[Rocket Lab @RocketLab]

LOX loading has begun on Electron and the lift-off time has been set for today's mission.

'Fasten Your Space Belts' for launch at:
🚀 NZDT | 12:17 pm
🚀UTC | 23:17
🚀 ET | 06:17 pm
🚀PT | 03:17 pm

📺: https://t.co/gj7BV5iw1W

[Rocket Lab @RocketLab]

We’re ready and rollin’ out to the pad for our launch for @BlackSky_Inc this week. Launch rehearsal is up next, then it’s onward to launch for our 60th Electron mission.

Mission info: https://t.co/xyg2Ght0jc