Clinical Trials AI

Immunai occupies a different position from most of this lane. It is not developing its own drugs. It sells pharmaceutical companies an understanding of the immune system, and it has been paid repeatedly for it. The platform has three named parts. AMICA, the Annotated Multi omic Immune Cell Atlas, is a proprietary clinically annotated single cell immunology database. AMICA-OS is the operating system layer combining that database with foundation models. The Immunodynamics Engine is the model of immune function itself. The data underneath spans single cell RNA, surface proteins, immune receptor repertoires and spatial gene expression, drawn from clinical and laboratory samples, and the stated uses are biomarker discovery, patient stratification, mechanism of action analysis and dose optimisation in drug development. The validation here is commercial rather than published, and it is unusually strong of its type. AstraZeneca began working with Immunai in late 2022 and has expanded three times: across oncology clinical programmes, then into inflammatory bowel disease in October 2025 in a deal worth up to $85 million for exclusive rights to a target Immunai had identified through the atlas, then again in May 2026 for up to $37.5 million across 2026 and 2027. Bristol Myers Squibb signed a multi year agreement in January 2026 and Boehringer Ingelheim followed in June 2026 for T cell target discovery. A partnership with the Parker Institute for Cancer Immunotherapy assembled what both parties describe as the largest single cell dataset for real world immunotherapy research, from 3,700 blood samples across 1,070 patients treated with checkpoint inhibitors. A sophisticated buyer returning three times, and paying for a target the model found, is a harder signal to manufacture than a case study. The company is headquartered in New York with offices in Tel Aviv, Prague and Zurich, employs more than 170 people, is led by chief executive Noam Solomon and has raised close to $270 million. What distinguishes this record within the lane is that the privacy and security axes genuinely apply. The chemistry led companies here train on molecules; this platform is built from patient samples with clinical annotation, and the atlas is enriched by work done for one partner and then used to serve others. That accumulation is the product's central advantage and also the question nobody has answered publicly.

Biofourmis monitors patients at home and tries to detect deterioration before it becomes an admission. The Biovitals analytics engine ingests continuous signals from clinical grade wearables, builds a personalised physiological baseline for the individual rather than comparing them to a population norm, and raises an alert when that person drifts from their own pattern. Biofourmis Care wraps that in a care at home offering for hospitals, health systems and payers spanning acute, post acute and chronic acuity, combining the algorithms with devices, in home service orchestration and virtual clinical teams. Biofourmis Connect applies the same monitoring apparatus to decentralised clinical trials for biopharma customers. BiovitalsHF, a heart failure product aimed at optimising medication dosing, received Breakthrough Device Designation in 2021. The corporate history is turbulent and a reader should have it. Founded in 2015 and originally based in Singapore, the company moved its headquarters to the United States in 2019 with about 60 employees and grew to roughly 650 including two acquisitions. It raised in the region of 460 million dollars across six rounds, including 100 million in 2020 and a 300 million dollar round in 2022 that valued it at 1.3 billion, backed by SoftBank Vision Fund, General Atlantic, Openspace, Bessemer Venture Partners, Intel Capital and CVS Health. In July 2023 it cut 120 roles globally, about 15 percent of the company, and the founding chief executive stepped down a month later. In October 2024 it merged with CopilotIQ, a Nashville company running high frequency connected care for older adults with hypertension and diabetes using continuous biomarker data, behavioural analytics and nursing visits by licensed clinicians. The transaction was all stock, existing investors put close to 100 million dollars into the combined business, and CopilotIQ's chief executive David Koretz leads the combined entity. Biofourmis continues to be sold under its own name with its own product lines, so the change of control does not alter how this record reads. Named customers include UCI Health, Lee Health, Community Health Network, Augusta University Health under a four year collaboration, and Orlando Health under a multi year agreement. A partnership with GE HealthCare announced in February 2024 was intended to extend that manufacturer's patient monitoring reach from the hospital into the home. Headquartered in Needham, Massachusetts. Two things a reader should weigh. A dedicated pass located no company announcement of any kind after the October 2024 merger, and the corporate website, while live and carrying a current copyright, still displays placeholder Latin text in its main navigation menus. Neither fact establishes anything about the health of the business, and both are things a buyer would want to ask about directly. And no pricing of any kind was located.

Vivalink sells the sensing and data layer that other companies build monitoring products on. Its Biometrics Data Platform combines medical grade reusable wearables with edge networking, cloud data services and a development kit, so a digital health company, a hospital at home programme or a clinical trial sponsor can capture continuous physiology without building the hardware or the pipeline. Sensors cover a multi function cardiac electrocardiography patch, a clinical temperature monitor, oxygen saturation and blood pressure, and the platform additionally ingests third party devices including glucose monitors and pulse oximeters from established manufacturers. The technical lineage is genuine. The company introduced a breathable thin film substrate with integrated circuits and sensors in 2014, developed in collaboration with Google's advanced technology group and launched commercially as a digital tattoo, and that substrate underpins the current sensor family. Regulatory and standards posture is the strongest part of this record and is enumerated rather than gestured at. Sensors carry clearance in the United States, the European Union and China. The platform is stated to comply with United States health privacy law, European data protection law, the federal rule governing electronic records and signatures in regulated research, and a stack of device standards covering quality management, medical device software lifecycle, risk management and biocompatibility, alongside the international information security management standard. Very few vendors in this index name an information security certification at all, and fewer still list the software lifecycle and biocompatibility standards that a skin adhering connected device actually needs. The business is enablement rather than end user software. More than 400 customers are claimed with brand reach across 116 countries, and named applications include ambulatory cardiac monitoring, hospital at home and decentralised clinical trials, with a partnership placing the technology inside a global trial infrastructure provider. Research use includes a longitudinal atrial fibrillation study of up to 3,000 subjects, a chronic obstructive pulmonary disease progression study, and sleep research. Founded in 2014 by Jiang Li and based in Campbell, California, operating as VivaLNK, Inc. Funding is poorly documented in public sources and the figures that circulate appear inconsistent with the company's stated commercial reach, so no total is asserted here. Two things a reader should weigh. This is closer to infrastructure than most records in this index, since much of the value is capturing and delivering data rather than interpreting it, and the clinical application is frequently the customer's. And no pricing of any kind was located.

Sibel Health makes soft, flexible sensors that stick to skin and monitor vital signs without a single cable. The ANNE platform pairs a chest sensor capturing electrocardiography, heart rate, respiratory rate, skin temperature, body position and activity with a limb sensor capturing photoplethysmography, oxygen saturation, pulse rate and temperature, feeding an application and central hub that display, alarm and support multi patient monitoring. A Northwestern University spinout founded in 2018, the company sits in the Chicago area with offices in San Diego and Seoul and operates in more than 20 countries. The population coverage is the widest in this index and is backed by separate clearances rather than by claim. ANNE Pediatrics is indicated for neonates including those born extremely premature. ANNE One covers adolescents from 12 and adults, in hospital and at home. ANNE Maternal, cleared in April 2026, is described as the first fully wireless platform for simultaneous maternal and fetal monitoring through labour, delivery and the postpartum period, streaming maternal vital signs alongside fetal heart rate and uterine contraction detection. A separate cough sensor, Aria, has been accepted into a federal qualification programme as a drug development tool, and a Discovery platform serves pharmaceutical clinical trials. Regulatory standing is extensive: at least eight United States clearances, with a seventh announced in March 2025 covering alarms, alerts and a central station, and European Class IIb certification under the current medical device regulation granted in June 2026. Two things distinguish this record from its peers. The sensors are cleared under an open medical device communication standard rather than a proprietary network, and the European certification was announced specifically as the first wireless wearable monitoring platform certified to key interoperability standards. A major patient monitoring manufacturer, which is also an investor and co development partner, cites that open standard as the reason for the collaboration, and the two were selected by the Capital Region of Denmark to deploy across Copenhagen hospitals. The second is bias. The company states it has validated the accuracy of its pulse oximeter across a wide range of skin tones, which addresses the single most documented measurement failure in physiologic monitoring, and that work sits alongside deployments in India, Pakistan, Nigeria and Rwanda with a United Kingdom university research unit, supported by a 17.5 million dollar philanthropic grant aimed at low resource settings. Series C financing reached 39 million dollars by October 2025 with total funding above 63 million, led by existing investors. Two dedicated passes located no pricing of any kind, no information security certification and no trust centre, and the published privacy policy is minimal.

Huma sells a regulated platform that other organisations configure into their own clinical software. The Huma Cloud Platform is a disease agnostic and device agnostic software as a medical device, cleared as a configurable framework rather than as a single product, so a hospital, national health system or pharmaceutical sponsor can assemble a regulated disease management tool from pre built modules with no code and deploy it in weeks rather than running a multi year regulatory programme of its own. Partners inherit the clearance. That clearance is the most extensive in this index. The platform holds simultaneous status across six jurisdictions: United States Class II under the 510(k) route, European Union Class IIb under the current medical device regulation, United Kingdom Class IIb registration, Australian, Saudi and Indian approvals, with a Health Canada Class II licence added subsequently. The United States clearance permits monitoring patients of any age with any condition, explicitly including paediatrics and pregnancy, and the platform is regulated to host artificial intelligence and machine learning models rather than only fixed logic. Five layers sit on that base: remote patient monitoring and companion apps, decentralised clinical trials, Hi Scribe for generative clinical documentation, an agentic layer marketed as Huma Intelligence, and direct to consumer virtual care. A software development kit lets partners embed functionality into their own products, and the hosting framework is described as cloud agnostic. Scale is substantial and geographically wide. Company material has reported more than 3,000 hospitals and clinics, over 1.8 million active users in care delivery and more than 650,000 research participants, with the platform used to build software across more than 70 countries. Published case work includes an emergency department triage deployment in a London hospital, a decade long oncology real world evidence study, a lung cancer screening programme validating a risk model that has become part of a national screening blueprint in Germany, a non interventional insomnia study across Germany and Austria, and a kidney and diabetes research programme that recruited 4,500 patients a year ahead of schedule. Huma Therapeutics Limited is based in London with New York operations and is led by founder and chief executive Dan Vahdat. Series D financing closed in July 2024 taking total funding past 80 million dollars, with investors including the venture arm of a major pharmaceutical group. Two things a reader should hold. The strongest asset here is regulatory and architectural rather than algorithmic: the platform's distinguishing property is that it is cleared and configurable, and much of the artificial intelligence running on it belongs to partners. And two dedicated passes located no pricing of any kind, no information security certification and no customer facing trust centre, with the clearest account of data handling appearing in a clinical trial protocol rather than in anything a prospective buyer would find.

Aetion is a real world evidence software company in New York, founded in 2012 by Harvard Medical School faculty in pharmacoepidemiology, and now operating as Aetion, a Datavant Company, inside Datavant's Life Sciences business following an acquisition completed on 11 July 2025. Its buyers are pharmaceutical and device sponsors, payers, health technology assessment bodies and regulators rather than clinicians, and it appears in no care delivery workflow. The product is Aetion Evidence Platform, a data agnostic analytic environment for designing and executing observational studies with pre specified protocols, locked analysis plans, parameter level transparency and audit trails. Named modules are Discover for exploratory analysis, Substantiate for regulatory grade descriptive and causal studies, Activate for data preparation and measure definition through low code tools and a hosted coding environment, and Generate. The company acquired Replica Analytics in 2022, adding synthetic data generation. The platform is offered through AWS Marketplace for deployment inside a customer's own cloud environment, and the stated post acquisition direction is for the evidence platform to sit above Datavant's linkage layer. The methodological record is the reason this vendor is unusual. Aetion was the industry partner in RCT-DUPLICATE, a demonstration project run with the Division of Pharmacoepidemiology and Pharmacoeconomics at Brigham and Women's Hospital and Harvard Medical School and with the United States Food and Drug Administration, which tested whether observational database studies could reproduce the findings of randomised controlled trials. Protocols were published in advance on a public trial registry, results appeared in Circulation in 2021 for the first ten emulations (doi 10.1161/CIRCULATIONAHA.120.051718) and in the Journal of the American Medical Association in April 2023 for the full set of 32 (doi 10.1001/jama.2023.4221), with FDA staff among the named authors. The project also predicted the results of ongoing trials before those trials read out. A subsequent oncology extension, ENCORE, runs with the FDA Oncology Center of Excellence across twelve trials in four cancers. A data errors correction to the omnibus paper was published in JAMA in April 2024. What that record establishes is conditional rather than promotional, which is what makes it useful: agreement between the observational studies and the trials was strong where the trial design could be closely emulated in routine care data, and diverged where it could not. The company has published the boundary of its own method rather than only its successes. One commercial fact belongs in front of any buyer running a competitive process. Aetion and Datavant are now a single corporate family, and independent buyer guidance advises treating them as one bidder rather than two. Datavant itself is screened out of this index as connectivity infrastructure and is recorded at [[datavant]] in the screening log rather than as a graded record.

Truveta is a collective of 30 United States health systems that pooled their patient records into one research dataset and own the company that runs it. Founded in 2020 and based in Bellevue, Washington, led by co founder and chief executive Terry Myerson, it holds de identified electronic health record data representing more than 120 million patients. Members include Providence, Advocate Health, Trinity Health, Northwell Health, CommonSpirit Health, Tenet Healthcare, Henry Ford Health, Ochsner Health, MedStar Health, Memorial Hermann and twenty others. The artificial intelligence is the Truveta Language Model, described as a large language multi modal model that normalises billions of data points from thirty different record estates into a single consistent structure, running on Microsoft Azure. Microsoft has invested in the company. Normalisation is the hard part of this business: the same diagnosis, drug and laboratory result are recorded differently in every system, and research is only possible once they agree. The company positions the result as regulatory grade safety and effectiveness data that can replace slow and expensive clinical trials and registries, and published work using it spans cardiovascular, neurology, oncology and metabolic research, including studies of GLP-1 medicines and methodological comparisons between claims and record data. In January 2025 members launched the Truveta Genome Project with the Regeneron Genetics Center and Illumina, which will sequence the exomes of an initial ten million volunteers and is described as more than ten times the scale of previous efforts, with explicit representation across ancestries, ethnicities, sex and social drivers of health as a design goal. Consent is obtained at the point of care to use leftover biospecimens from routine laboratory tests, which are sent for sequencing and linked to de identified records, with remaining material stored for future multi omics work. Health systems, Regeneron and Illumina invested 320 million dollars in preferred equity at a valuation above one billion dollars, Regeneron contributing 119.5 million and Illumina 20 million.

Averbis is a Freiburg company that turns unstructured German and multilingual clinical text into structured, coded data. It was founded in 2007 as a spin out from the University Medical Center Freiburg and states it works with more than 100 hospitals and partners in Germany and abroad, with more than 15 years in the field. The flagship is Health Discovery, an on premise medical text mining platform offering more than 50 ready made annotators that extract diagnoses, medications, laboratory values and other facts from nursing narratives, pathology reports and physician letters, mapping each finding to codes from a curated terminology containing millions of medical terms. Alongside it sit Medical Summary, Docs2FHIR for structured handoff, Medical Dialog, and a Healthcare Cloud application interface with a free tier covering German medical text and a limited entity set. The technical description is more specific than most vendors offer. The company names the underlying text mining engine it builds on, describes an indexing technique it calls Morpho Semantic Indexing, and details linguistic capabilities that matter disproportionately in German, including medical stemming and decompounding, since German medical vocabulary forms long compound words that defeat naive tokenisation. The extraction also returns semantic interpretation rather than bare terms, including whether a diagnosis is confirmed or negated and whether a laboratory value falls outside range. Stated applications span clinical decision support, research, automated billing and coding, rare disease detection, cohort selection and clinical trial recruitment. A distinctive commercial position is that a substantial part of the customer base is other software companies: hospital information system providers, health portals, medical publishers and pharmaceutical firms embed the extraction inside their own products, with a named partnership with the hospital information system vendor Meierhofer. Academic relationships include the Chair of Medical Informatics at the Technical University of Munich and the Bosch Health Campus in Baden Wuerttemberg, and the company states its expertise has contributed to well over 100 publications.

Deciphex is a Dublin company founded in 2017 by Donal O'Shea, its chief executive, and Mark Gregson, addressing the shortage of pathologists rather than the accuracy of any single diagnosis. Its chief medical officer is Runjan Chetty. It has raised roughly 56 million dollars in total, including a 31 million euro Series C in January 2025 led by Molten Ventures with ACT Venture Capital, Seroba, Charles River Laboratories, IRRUS Investments, the HBAN Medtech Syndicate and Nextsteps Capital. The business has two halves and a buyer should understand which one they are purchasing. Patholytix is software: a non clinical workflow platform for toxicologic and preclinical pathology, used by pharmaceutical and biotechnology companies during drug safety assessment. In April 2024 Charles River Laboratories, the largest preclinical research organisation in the sector and also an investor here, launched Patholytix Foresight jointly with Deciphex, a decision support tool built on Patholytix 4.0 that pairs artificial intelligence classifiers with whole slide images to speed primary evaluation and peer review. The two extended that into an exclusive image management arrangement in February 2025. Diagnexia is the other half and it is a service rather than a product: a network of more than 250 subspecialty pathologists who report cases digitally for healthcare providers, positioned explicitly against the traditional locum model, with a research variant called Diagnexia Analytix serving drug development. This record is scoped principally to the software, since Patholytix is separately licensable while Diagnexia is a staffed diagnostic service, and both are described here because the artificial intelligence and the human network are sold together. The company states its platforms let pathologists work up to 40 percent faster while maintaining accuracy, is expanding across the United States, United Kingdom, European Union, Canada and Japan, holds a partnership with Novartis on artificial intelligence for drug discovery pathology, and has stated it will use its image repository to build pathology foundation models.

Aignostics builds foundation models for computational pathology and sells their output to biopharmaceutical companies for drug discovery, translational research, clinical trials and companion diagnostic development. It was established in 2018 inside Charité Universitätsmedizin Berlin and the Berlin Institute of Health, alongside TU Berlin and Fraunhofer HHI, and spun out in 2020. Founders include Frederick Klauschen of Charité, Viktor Matyas and Maximilian Alber. It is based in Berlin with a New York presence and more than 75 staff. The models are the product and they are documented in public preprints rather than in marketing copy. RudolfV, the first, was built on a deliberately heterogeneous dataset drawn from more than 15 laboratories covering 58 tissue types and 129 histochemical and immunohistochemical staining modalities, with pathologist knowledge built into the curation rather than applied afterwards. Atlas followed, developed with Mayo Clinic and Charité, a vision transformer of roughly 632 million parameters trained on 1.2 million whole slide images from more than 490,000 cases, sampled into about 520 million tiles at four magnifications, and evaluated against 21 public benchmarks alongside named rival models. Atlas 2, announced January 2026 with Mayo Clinic, LMU Munich and Charité, is around 2 billion parameters trained on more than 5 million slide images and reports the highest average performance across 80 public benchmarks, with distilled smaller versions released for compute constrained settings. The most recent product, Atlas H&E-TME, is a self service application profiling the tumour microenvironment at single cell resolution from routine stained images. The company states that Atlas 2 ships with clinical grade regulatory documentation intended to support integration into medical devices built by others. More than 55 million dollars has been raised including a 34 million dollar Series B in October 2024, with ATHOS, Wellington Partners and the Boehringer Ingelheim Venture Fund among investors. Development partnerships are named with Bayer and Mayo Clinic.

Anumana builds neural network algorithms that read a standard electrocardiogram to detect disease the trace was never thought to reveal. It was founded in 2021 as a joint venture between Mayo Clinic and the health data company nference, and is based in Cambridge, Massachusetts. Mayo Clinic co founded the company and holds a financial interest in it, which the company discloses in its announcements. The premise is that an inexpensive, century old test contains signal beyond what a human reader can extract. The platform is stated to be built on more than 22 million patient records spanning more than 20 years, obtained through exclusive partnerships with academic medical centres, and the flagship low ejection fraction model is described as developed from roughly 2.9 million paired electrocardiogram and echocardiogram studies across more than 676,000 patients. Three algorithms have been cleared by the Food and Drug Administration. ECG-AI LEF detects low ejection fraction and is available in the United States and the European Union. ECG-AI PH, cleared March 2026, detects pulmonary hypertension and is the first such algorithm cleared for use with a standard 12 lead electrocardiogram. A cardiac amyloidosis algorithm was cleared in April 2026 and is stated to be the first and only one for that indication on a standard 12 lead trace. Several algorithms have held Breakthrough Device Designation, and the amyloidosis product was selected among the first 15 devices in the agency's Total Product Life Cycle Advisory Programme pilot. The company raised a 25.7 million dollar Series A led by its two founders alongside Matrix Capital Management, Matrix Partners and NTTVC, and acquired the cardiac electrophysiology data company NeuTrace in 2022. It runs algorithm development collaborations with Novartis, Johnson and Johnson and Pfizer.

Layer Health is a Massachusetts Institute of Technology spin out applying large language models to clinical chart review, founded in 2023 and based in Boston. Its co founders are David Sontag, an MIT professor of machine learning in healthcare who serves as chief executive, with Monica Agrawal, Luke Murray and Divya Gopinath, alongside Steven Horng, an emergency physician and clinical informatician at Harvard Medical School. The first product is called Distill. Rather than summarising a chart for a clinician about to walk into a room, it performs structured abstraction: reading unstructured notes, labs and imaging across a patient's record and extracting the specific fields a downstream process needs, with each extracted field linked back to the evidence in the record that produced it. The stated applications are clinical registry submission, quality measurement, curation of real world evidence, clinical documentation improvement and revenue cycle. The company states the platform works without requiring labelled training data, which is the usual bottleneck in this work. Registry abstraction is the wedge. Hospitals employ nurse abstractors to read charts manually and submit data to national registries in cardiovascular disease, oncology, surgery and other areas, and the work is slow and expensive. Named deployments include White Plains Hospital, Froedtert, and Intermountain Health, which took a strategic investment through Intermountain Ventures and committed to a multi year deployment across 33 hospitals starting with stroke, bariatric surgery and cardiovascular registries. The company also works with the American Cancer Society on abstraction of patient data drawn from across the United States for research. It raised a 4 million dollar seed round in November 2023 from GV, General Catalyst and Inception Health, followed by a 21 million dollar Series A in March 2025 led by Define Ventures with GV and Flare Capital Partners.

Guardant Health is a publicly traded precision oncology company, listed on Nasdaq as GH, founded in 2012 and based in Palo Alto, California, led by co chief executives Helmy Eltoukhy and AmirAli Talasaz. It sells blood and tissue based cancer tests across four stages of care: screening the average risk population, selecting therapy in advanced disease, monitoring for recurrence, and supporting biopharmaceutical development. The therapy selection product is Guardant360. Guardant360 CDx was the first liquid biopsy approved by the Food and Drug Administration for comprehensive genomic profiling, and by January 2026 carried its 25th companion diagnostic indication. In May 2026 the agency approved Guardant360 Liquid CDx, which the company describes as the largest approved liquid biopsy panel, assessing a genomic footprint 100 times wider than the previous version and combining genomic with epigenomic profiling from a single blood draw. The seven companion diagnostic indications on the earlier test transferred to it. A separate Guardant360 Tissue product is a laboratory developed test run under the company's own clinical laboratory certification and is not approved by the agency, which is a distinction buyers frequently miss. The screening product is Shield, approved in July 2024 as the first blood test for primary colorectal cancer screening. It was granted Advanced Diagnostic Laboratory Test status by the Centers for Medicare and Medicaid Services, was added to the American Cancer Society colorectal cancer screening guidelines in 2026, and received a UnitedHealth Group coverage decision effective 1 August 2026. Guardant Reveal covers recurrence monitoring and holds Medicare coverage for colorectal cancer through the molecular diagnostics services programme. The company describes an artificial intelligence layer called the Smart Platform, and a branded capability called InfinityAI. More than one million blood tests have been performed.

Digital cognitive assessment built on machine learning analysis of drawing and speech behaviour rather than on digitised test scoring, which is the distinction that separates it from most of this category. The flagship DCTclock analyses the entire process of drawing a clock, capturing temporal and spatial features of stylus manipulation across the whole drawing rather than scoring the finished picture, and extracts cognitive and motor metrics no paper version can produce. Digital Clock and Recall (DCR) adds immediate and delayed word recall to assess verbal memory, runs in about three minutes, and the LinusAD algorithm combines age, APOE status, drawing metrics, speech and acoustic features and stylus dynamics. The suite now exceeds a dozen assessments including a digital Trail Making Test Part B, a Digital Assessment of Cognition, gait and speech measures, and the electronic Person Specific Outcome Measure. Technology originated in over a decade of R&D at Lahey Hospital & Medical Center and MIT. The commercially important capability is biomarker prediction, which puts this product in a different business from cognitive screening: peer reviewed work found DCTclock significantly correlated with amyloid PET in cognitively normal individuals and outperforming the 30 minute Preclinical Alzheimer's Clinical Composite at distinguishing amyloid positive from amyloid negative, a Harvard Aging Brain Study longitudinal cohort of over 200 cognitively normal adults found higher amyloid or tau burden associated with faster DCTclock decline, and in the 930 participant Bio-Hermes-001 study the DCR predicted amyloid PET status. The company also reports the DCR predicting plasma p-tau217 status. That matters because disease modifying Alzheimer's therapies require confirmed amyloid pathology, so a three minute office test that predicts PET status addresses the screening failure and prescreening cost problem directly. Deployed to health systems with EHR integration and a remote administration option. Note the company's own positioning acknowledges the complementary rise of FDA cleared blood based biomarkers rather than competing with them.

New York company applying agentic AI to clinical trial data operations, the unglamorous layer beneath drug development where trial data must be cleaned, reconciled, reviewed, and reported before a submission can reach regulators. Combines large language models with deterministic clinical algorithms under an explicitly human in the loop design, integrating with existing clinical systems rather than replacing them, and sells to pharmaceutical sponsors and contract research organizations. A controlled study of 10 medical reviewers published August 2025 reported roughly sixfold higher data cleaning throughput, reviewer error rates falling from about 54.7 percent to 8.5 percent, and roughly fifteenfold fewer false positive queries. Raised a 3 million dollar seed round in July 2026 led by Surface Ventures, following earlier investment from the venture arm of Swiss pharmaceutical company Debiopharm.

San Francisco company whose Digital Twin Generators are generative models trained on historical control and observational data to forecast how an individual trial participant would progress under control or standard of care. That forecast becomes a prognostic score used as a covariate in the trial analysis, a method the company calls PROCOVA, which reduces variance and can lower required sample size without introducing the confounding bias that external control arms carry. Occupies a regulatory position no other vendor in this index holds: PROCOVA received a positive qualification opinion from the European Medicines Agency in September 2022 as an acceptable statistical approach for primary analysis in Phase 2 and 3 trials with continuous endpoints, and FDA CDER subsequently commented that it concurs and that the method does not deviate from current guidance.

San Jose company whose Hypercube platform abstracts and reasons over unstructured patient records for chart review, cohort building, and clinical trial prescreening. Its stated technical differentiator is a hybrid approach pairing large language models with symbolic reasoning over a clinical hypergraph, adopted specifically because the company argues pure language model approaches are inadequate for clinical work given hallucination risk. Every answer is traced back to discrete highlighted evidence in the patient's original record, and the platform is cloud agnostic and can be hosted in the customer's own environment so data never leaves. Subject of prospective evaluation at the University of Pennsylvania comparing AI alone, human alone, and human plus AI trial prescreening workflows.

Tel Aviv company that simulates clinical trial outcomes before a trial is run, letting development teams test thousands of protocol variations against endpoint success, feasibility, and commercial impact. Its Large Real-World Drug Model is described as a clinical trial foundation model trained on real world data spanning more than 350 million patients, used to predict individual patient response to an investigational therapy and aggregate those predictions into a simulated trial result formatted like an actual readout. The company reports simulating more than 350 trials across 23 therapeutic areas with up to 90 percent predictive accuracy on primary endpoints, figures which are vendor stated and not independently verified.

New Mexico based digital pathology company whose HALO AP Dx is an enterprise platform FDA cleared for primary diagnosis of surgical pathology slides, with clearances tied to specific scanner hardware: K232833 with the Hamamatsu NanoZoomer S360MD and K252762 adding the Leica Biosystems Aperio GT 450 DX. Operates as both a diagnostic workspace and an algorithm host, with third party AI available through an associated store, positioning it alongside Proscia and PathAI as platform infrastructure rather than a single algorithm vendor. The company maintains a deliberate two product split in the United States: HALO AP Dx for clinical primary diagnosis, and HALO AP as research use only, explicitly not FDA cleared for diagnostic use.

Publicly traded Finnish deep learning pathology company offering cloud based image analysis across both clinical diagnostics and preclinical research. Holds IVDR certification and describes itself as Europe's leading provider of CE-IVD marked digital pathology AI, with clinical suites spanning breast, lung, prostate, colorectal, and gastric cancer plus lymph node metastasis detection. Recent models are built on a foundation engine designed to perform across real world variation in sample quality, staining, and scanning.

Digital pathology company whose AISight image management system holds FDA 510(k) clearance for primary diagnosis, paired with a large portfolio of AIM interpretation modules covering commercially significant oncology biomarkers. Its AIM-MASH tool became the first AI powered pathology Drug Development Tool to receive FDA and EMA qualification, allowing pharmaceutical sponsors to use it for endpoint assessment in registrational trials. Sold its diagnostics laboratory business to a national reference lab in 2024 while licensing the platform back, and entered a definitive merger agreement with Roche in May 2026.

Precision research platform applying AI and natural language processing to structured and unstructured EMR data, including physician notes, pathology, genomics, and lab reports, to match patients and sites to trial protocols in real time. Connects health systems, treating physicians, sponsors, and CROs in a shared ecosystem covering cohort building, site feasibility, patient recruitment, and real world evidence generation. Reports sites finding more than 25 percent additional patients relative to traditional recruitment. Acquired in March 2025 by Tempus AI, a company listed on the Nasdaq, for undisclosed consideration; at the time of the transaction the platform was reported to connect more than 750 provider sites, and the acquirer described the attraction as the integration infrastructure. This record covers the Deep 6 platform. Contracting, assurance and governance questions now run to the parent, and a buyer should establish which entity signs and whether the platform has been migrated onto the parent's infrastructure.

Digital pathology software company whose Concentriq platform manages and analyzes whole slide pathology data for clinical laboratories and life sciences organizations. Its diagnostic edition is FDA 510(k) cleared and CE-IVDR marked for primary diagnosis, while the research edition remains labeled Research Use Only, a distinction the company draws explicitly. Embedded AI recommends stain panels and ancillary tests from tissue appearance and scores image analysis biomarkers including PD-L1, HER2, and Ki-67 in the viewer.

Medically specialized AI company whose Synapsis AI platform automates electronic medical record chart review and abstraction, answering specific clinical questions from structured and unstructured records rather than generating summaries. Applied to clinical trial pre screening, observational studies, registry reporting, and quality measurement. Deployed enterprise wide at a major academic health system, with results published in a peer reviewed cardiology journal.

Clinical trial platform that deploys AI matching inside provider EHRs to identify trial eligible patients within routine care, combining structured data prefilters with large language models that reason over full text clinical notes and nuanced eligibility criteria. Pairs the technology with recruitment coordinators working alongside site teams, plus site feasibility automation and a trial design service for sponsors. Operates a research ready provider network spanning community oncology practices, health systems, and academic cancer centers, described by the company as covering roughly 2,100 care locations across the United States, Japan and Israel. Its Study Conduct platform uses source linked electronic case report forms with integrated source viewers, so monitors validate data against the originating clinical record. In April 2026 the company announced a research collaboration with the United States Food and Drug Administration under which trial data is analysed and key safety and efficacy signals are reported to sponsors and to the agency in near real time, already operational in a Phase 2 and a Phase 1b trial, with Amgen and AstraZeneca the first sponsors to join; the company describes itself as the sole technology provider operationalising the agency's Real-Time Clinical Trials proof of concept studies. It also announced a partnership with the contract research organisation Parexel in late 2025. Founded and led by Kent Thoelke, previously Chief Innovation Officer at ICON and Chief Scientific Officer at PRA Health Sciences; incubated by ARCH Venture Partners.

Spatial biology company applying computer vision and machine learning to tissue imaging, integrating high plex spatial proteomics, histopathology, and clinical data to identify predictive spatial biomarkers. Positioned primarily for pharmaceutical R&D, supporting patient stratification and trial enrichment for antibody drug conjugates, bispecifics, and immunotherapies, with an emerging diagnostics application. Reported as the first spatial AI tool used by pathologists for clinical trial patient selection tied directly to a drug development program.

Respiratory diagnostics company developing Sylvee, a chest worn wearable that uses patented active acoustic resonance, projecting low frequency sound into the lungs and analyzing the returning signal with machine learning, to measure lung structure and function. Positioned to replace effort dependent spirometry with a passive test and to enable continuous home monitoring for COPD and small airway disease. Backed in part by NIH small business funding; the device is investigational and not FDA cleared.

Commercial spinout of the nonprofit research lab FutureHouse, building an autonomous AI research platform for scientific R&D. Its flagship agent Kosmos runs extended research campaigns that read literature, execute analysis code, generate hypotheses, and return fully cited reports. Buyers are biopharma and biotech R&D organizations rather than providers, and the platform is sold on a credit model with an academic free tier.

Precision oncology company operating hospital linked genomics laboratories across India, Dubai, Nepal, and the Philippines, paired with OncoTwin, an AI clinical decision support platform that draws treatment insights from real world clinico genomic and outcomes linked data. Its stated thesis is that most genomic reference data represents Caucasian populations, and it builds population specific panels for South Asian and other underrepresented groups.

Oncology AI reading the full patient chart, founded 2021 on the observation that while software could already handle the roughly 20 percent of medical data that is structured, generative AI made the other 80 percent, the free text notes, tractable. OncoLLM is the underlying platform and the architecture is disclosed with unusual specificity: not one model but a constellation of eight specialized models ranging from 3 billion to 72 billion parameters, working agentically to interpret information at the patient level. Prism is the trial matching application, screening patients with upcoming appointments against all active trials and working in both directions, patient to trial and trial to patient, with continuous tracking. Matches are cited back to pathology, biomarkers, and note level evidence rather than returned as a bare recommendation. The platform has expanded beyond matching into verifiable patient summaries for visit preparation, cancer registry abstraction, and structured data generation for research. Reported results include a 40 percent increase in trial matches, more than 30 percent increase in enrollments, and 67 percent reduction in chart review time, with one NCI designated center reporting 100 percent screening coverage at three times the throughput of manual review. Peer reviewed validation has appeared in Nature Digital Medicine with presentation at ASCO, and a pilot study at the Medical College of Wisconsin Cancer Center covers gastrointestinal, genitourinary, breast, and thoracic teams. Mount Sinai Tisch Cancer Center deployed Prism in January 2026, becoming the first NCI designated Comprehensive Cancer Center in New York City to use it for systemwide matching. More than $36 million raised; co-founders Sarim Khan and Hrituraj Singh.

AI intelligence platform for life sciences medical affairs, scientific communications, and drug safety, which places it on the medical rather than commercial side of pharma and distinguishes it from vendors excluded from this index for pharmaceutical marketing. The Sorcero Intelligence Platform reads across a reported 263 million publications and 1.3 billion citations globally alongside congress sessions, reports, surveys, CRM interactions, safety cases, and medical inquiries, identifying which key opinion leaders and clinicians are active in specific research areas or treating relevant populations. Sorcero Medical serves medical affairs, with Field Medical Excellence and Insights including an iPad capture app and Congress Intelligence with scientific abstract integration, both introduced March 2026. Sorcero Safety, built with Springer Nature, covers literature and adverse event monitoring for pharmacovigilance. Sorcero MedTech came from the July 2025 acquisition of Axiom Health, extending the platform to medical device real world data and making it a unified platform across pharmaceutical and device organizations. The company describes a trust first approach with hallucination prevention and validated outputs, and an agentic architecture using specialized agents to validate medical information. Reported adoption is a third to 40 percent of the top 30 global pharmaceutical companies. Named a Leader in AI enabled pharmacovigilance software by CB Insights alongside IQVIA, Veeva, and Oracle. Six foundational medical AI patents; 2025 Google Cloud Partner of the Year for Healthcare and Life Sciences. $59 million raised in total including a $42.5 million Series B in November 2025. Co-founded and led by Dipanwita Das.

Indexed for the AI platform and agent portfolio rather than for the wider clinical research services, data, and consulting business, which is context under this index's product scoping rule. IQVIA (NYSE: IQV) launched IQVIA.ai in March 2026, a unified agentic platform and agent marketplace spanning clinical, commercial, and real world operations, built on the company's proprietary health data and Healthcare grade AI together with NVIDIA Nemotron, NeMo Agent Toolkit, Dynamo, and LangChain, following a collaboration begun over a year earlier. Disclosed agent use cases include target identification, clinical data review, literature review, market assessment, and healthcare professional engagement. The company reports filing more than 100 AI related patents and deploying more than 150 intelligent agents across internal teams and client environments, with 19 of the top 20 pharmaceutical companies having begun incorporating IQVIA agents into their workflows. IQVIA AI Assistant is a generative interface over the company's existing solutions and data products. The commercial side of the portfolio includes healthcare professional targeting and engagement, which sits closer to pharmaceutical marketing than to clinical operations and should be evaluated separately from the research and clinical agents.

Indexed for the AI capabilities inside the Veeva Vault platform rather than for the platform itself, which is context under this index's product scoping rule. Veeva (NYSE: VEEV) is the dominant software platform for life sciences, spanning clinical, regulatory, safety, quality, medical, and commercial, with customers including Novo Nordisk, Gilead, Bristol Myers Squibb, Merck, Roche, Moderna, and BioMarin. Veeva AI Agents became available in December 2025, initially for Vault CRM (Free Text Agent flagging issues in call notes, Voice Agent for spoken input, Pre-call Agent assembling context) and PromoMats (Quick Check Agent scanning promotional content against brand and regulatory guidelines before medical, legal, and regulatory review, and Content Agent assisting reviewers). Agents are built on large language models from providers including Anthropic and Amazon, hosted on Amazon Bedrock but operating inside the Vault environment, accessible through the Vault interface or API and customizable through Veeva's AI framework. Safety and quality agents are reported live, with clinical and regulatory agents tied to the 26R2 release. Availability matters here and is stated rather than blurred: two further announced product lines are not yet available. Falcon, a separate platform for standardized agentic labor covering trial master file intake, safety case processing, and health authority interaction management, targets late 2026 for early adopters, and Agentic Authoring, which drafts submissible regulatory documents, is expected in late 2027. Neither is indexed as a shipping capability.

Indexed for the AI capabilities layered across the Medidata clinical trial platform rather than for the platform itself, which is treated as context under this index's product scoping rule. A Dassault Systemes brand, the underlying platform spans more than 38,000 trials and 12 million patients across roughly 2,300 customers and over one million registered users, anchored by Rave EDC. The AI products indexed here: Clinical Data Studio, an AI data quality management workspace that integrates Medidata and non Medidata sources, identifies data issues and safety signals, and is reported by one named customer to deliver up to 80 percent faster data review; Medidata AI Study Build within Designer, which automates study construction; and an AI imaging capability introduced at ASCO 2026 using proprietary algorithms including automated text detection that the company reports makes protected health information redaction 32 percent faster. Health Record Connect uses FHIR and health information exchanges to pull patient health records into trial data capture, reducing manual re entry at sites. The company reports its AI has supported more than 500 clinical studies over a decade, with more than 120 AI supported studies starting in 2025. Named customers for the AI products include Eisai.

AI platform for clinical data management and trial operations, sold to pharmaceutical and biotech sponsors. The Life Science Analytics Cloud is reported in use across more than 1,500 studies at over 50 pharma and biotech companies, and the company states its platform supported the trial behind the first COVID-19 vaccine. Core modules include Data Hub for harmonizing trial and real world data, Smart Data Quality which automates data review and query generation, Patient Insights, and Source to Submission which auto generates regulatory submission artifacts. An embedded generative AI co pilot writes and tests the code for cross domain data quality checks, removing manual programming from trial setup. In September 2025 the company introduced modular Clinical AI Agents built on its Agentic AI Framework, spanning study start to submission and designed explicitly to operate on partial autonomy with human oversight and controls, capable of independent reasoning, planning, and execution. Reported model depth is over 90 to 100 specialized models trained on life sciences data. Customer reported results with Pfizer include query handling time reduced by roughly 90 percent, data transformation time by roughly 50 percent, and submission timelines by roughly 35 percent. Named AI based Life Sciences Solution of the Year in the 2026 AI Breakthrough Awards, a third such recognition. Received a strategic growth investment of up to $430 million led by Carlyle with Amgen Ventures, Merck Global Health Innovation, McKesson Ventures, Pfizer Ventures, and Northpond participating.

Real world evidence generation, spun out of Stanford's Green Button project in 2020 and built to answer the question a clinician actually has at the bedside when no trial covers their specific patient. GENEVA OS is the underlying operating system across a federated network the company describes as exceeding 300 million anonymized patient records. ChatRWD is a chat based application that generates publication grade observational studies in minutes rather than months, without requiring a data scientist in the loop, and Green Button remains as a consultation service delivering evidence within 48 hours. Alexandria is the company's evidence library of pre computed evidence briefs. Two design decisions distinguish it: ChatRWD is an LLM independent framework, so an institution can maintain its own model security posture, and every answer carries a Real World Fitness Score rating how fit for purpose the underlying dataset was for that specific question, which is an explicit and unusual admission that evidence quality varies by question. Stanford Health Care has moved from using the service to embedding it in physician workflow and clinical notes. The Atropos Evidence Agent is distributed via the Databricks Marketplace under a partnership announced June 2025.

Tech bio company combining biological large language models, multimodal patient data, and agentic software. The Owkin K co pilot has two environments: K Navigator, an agentic research environment free to academic researchers that accelerates literature review across 26.5 million articles and 19 biomedical databases and explores spatial multiomic patient data, and K Pro, an enterprise co pilot that uses a single orchestrator to select and combine specialized biological AI skills across drug discovery and development. Both are powered by Owkin Zero, a fine tuned biological reasoning model. The company reports K Pro accelerating internal drug target identification from more than 12 months to roughly 3 months, validated through collaborations with AstraZeneca, Bristol Myers Squibb, and Sanofi, including a three year AstraZeneca licensing agreement to build biopharma agents. Owkin operates a group of entities spanning a biology foundation model (Bioptimus), diagnostics (Waiv), and a clinical stage drug program (Epkin); this record covers the software platform. Its CE-IVD marked pathology diagnostics, RlapsRisk BC and MSIntuit CRC, are indexed separately as Owkin Dx. Founded 2016 by Thomas Clozel, MD and Gilles Wainrib, PhD.

AI models of tumor and immune biology applied to precision oncology, serving both clinical care and drug development. The Tumor Portrait test integrates DNA and RNA exome sequencing into a single end to end assay, approved under CLIA, CAP, and the New York State Department of Health, producing tumor driver, microenvironment, and actionable biomarker characterization from one sample. Kassandra is the company's cell deconvolution model for reconstructing tumor microenvironment composition. Clinical and analytical validation was published in Communications Medicine, part of the Nature portfolio, across more than 2,200 tumors, reporting high reproducibility and clinical actionability in 98 percent of cases. Research collaborations span MD Anderson Cancer Center, Weill Cornell Medicine, and the Parker Institute for Cancer Immunotherapy, with nine abstracts accepted at ASCO 2026, and biopharma partnerships include Takeda for trial design and biomarker signature identification. A Japan joint venture operates with NEC Corporation and Japan Industrial Partners.

Two businesses under one name, and the balance between them has shifted decisively. The company today describes itself as a healthcare technology and services company powering the acceleration of clinical research, and its main navigation is entirely about that network; the device sits in a footer link. SKOUT is a real time computer aided polyp detection device that received FDA 510(k) clearance in 2022 for adults undergoing colorectal cancer screening or surveillance, applying computer vision to endoscopic video to flag suspicious tissue during the procedure. In a randomized controlled trial published in Gastroenterology, SKOUT demonstrated a 27 percent relative increase in adenomas detected per colonoscopy, and the company states it was evaluated in the largest US based multicenter clinical study completed for a computer aided detection device in this category. The vendor reports the device does not extend total procedure or withdrawal time. Distribution runs through an exclusive partnership with Provation, a GI documentation vendor reporting more than 3,500 customer facilities, so for many buyers the commercial counterparty is the distributor. The larger business now is a multispecialty clinical research site network. Iterative Health owns and operates research sites and embeds research into partner provider organisations, using machine learning for patient pre screening and eligibility identification alongside centralized operations and staffing. The network spans more than one hundred sites across North America, Europe, India and Australia, with more than forty pharmaceutical, biotech, device and contract research organisation partners, and the company reports twice the industry benchmark for site activation speed and three times the enrollment rate in inflammatory bowel disease trials. It closed a 77 million dollar Series C in April 2026 led by Intrepid Growth Partners and GV, having entered obesity and cardiology during 2026, appointed a chief medical officer for hepatology and obesity in February 2026, partnered with GI Alliance, One GI and US Heart and Vascular, and acquired three cardiology research sites in Texas in May 2026. Headquarters in Cambridge, Massachusetts and New York. A buyer should treat these as separate propositions. The device covers one procedure in one specialty. The research network covers four specialties, owns physical sites, and does not involve the device. The compliance questions differ sharply between them and are discussed on the regulatory, stewardship and posture axes.

Real world data company built on records patients choose to contribute, indexed for the life sciences data platform rather than the free consumer application, which is the collection mechanism rather than the product sold. Patients use a free app and web platform to aggregate their records from more than 50,000 US healthcare providers across Epic, Oracle Health, athenahealth, Quest, and the VA, then consent to contribute de identified data for research. Novellia's AI stitches those fragmented sources into structured longitudinal patient journeys spanning a reported 15 to 20 years, which the company positions against conventional real world data assembled by brokers from claims and partial hospital records. Buyers are biopharma teams in HEOR, market access, clinical operations, and medical affairs; the company reports customers among a majority of the top 10 to 15 global pharmaceutical companies. Raised an $18 million Series A led by Spark Capital in June 2026, bringing total funding to $28 million. Founded by Shashi Shankar, previously at Genentech working on real world data.

Clinical trial technology platform combining decentralized trial execution and electronic clinical outcome assessment with an agentic AI layer added in 2026. Agent Studio is a no code agent builder the company describes as the first agentic AI platform purpose built for clinical development, letting sponsor teams configure agents for protocol development, trial planning, and data workflows, with human in the loop validation and integration across life sciences systems. Shipped agents include TMF Agent for trial master file document management, announced January 2026, and a Digital Data Flow Agent that converts trial protocols into machine readable data. The underlying platform is reported deployed in nearly 400 trials across 70 countries and 120 languages, serving more than one million patients, and was named a Leader in eCOA by Everest Group. Founded 2014; CEO and cofounder Dr Michelle Longmire.

AI platform that retrieves, aggregates, and structures fragmented medical records into longitudinal patient histories, originally built for oncology and since extended to all therapeutic areas. The Clinical Clarity Engine applies natural language processing and machine learning to unstructured records; the company reports processing more than 300 million medical records from over 550,000 healthcare locations, with every structured output linked back to its source document. The xDECIDE provider portal presents structured data, autogenerated summaries, and AI assisted treatment option reports with scientific rationale, ranked by the xCORE engine and reviewed through a virtual tumor board; xINFORM is the patient facing portal. Data products supply longitudinal real world oncology datasets to research and regulatory programs. Holds HITRUST e1 certification. Raised a $46 million Series B in June 2026.

Precision health technology company, indexed here for its business to business products rather than its consumer app. Lightpath is an AI enabled chronic care management program sold to health plans, employers, and pharmacy benefit managers, using agents to triage and escalate members to a clinical team of physicians, pharmacists, and dietitians, with Lightpath Metabolic covering diabetes, prediabetes, and obesity. Workbench is a research data environment used by the NIH All of Us Research Program, the Michael J. Fox Foundation, and Helix. Sightline is a wastewater based epidemiology program for early infectious disease detection. The free Verily Me consumer application is outside the scope of this record. Formerly an Alphabet subsidiary; became an independent company in March 2026 alongside a $300 million investment round.

Generative AI drug discovery company (HKEX: 3696) operating both as a platform vendor and a clinical stage biotech. Pharma.AI comprises PandaOmics (AI target identification and indication prioritization), Chemistry42 (generative molecular design using generative tensorial reinforcement learning rather than library screening), and inClinico (clinical trial outcome prediction). The platform's flagship validation is rentosertib, a TNIK inhibitor for idiopathic pulmonary fibrosis where AI selected the target, generated the molecule, and informed trial design: it entered a 320 patient Phase III trial in July 2026, with discovery published in Nature Biotechnology and Phase IIa results in Nature Medicine. The vendor reports reaching preclinical candidate nomination in 12 to 18 months on average against a 2.5 to 4 year industry norm, and 13 programs cleared for IND.

AI clinical trial matching and enrollment platform for oncology. SYNERGY-AI extracts structured information from patient records including biomarker data and matches against a reported 19,000+ active oncology and hematology trials, with matches audited by certified oncology case managers before use. The platform includes physician and patient facing assistants and a trial enrollment orchestration layer (TrialRelay). Peer reviewed evidence is unusually strong for this category: a prospective evaluation in 3,804 metastatic cancer patients published in ESMO Real World Data and Digital Oncology reported matching four times faster than conventional methods using a neuro symbolic, multi agent architecture with an oncology specific knowledge graph. Reports 200,000+ onboarded patients and customers spanning pharma, CROs, and community oncology practices.

Precision medicine company (NASDAQ: TEM) whose provider software is what this index covers: Next, an AI clinical decision support system that alerts clinicians to patients who may have fallen off care guidelines, backed by a vendor reported 662 patient prospective study across six sites; Hub, a physician platform rebuilt on an agentic architecture including a prior authorization agent; and David, a generative AI clinical assistant deployed directly into the EHR, with Northwestern Medicine as the first health system. Tempus acquired Deep 6 AI in March 2025, adding a precision research platform that applies natural language processing to structured and unstructured EMR data to match patients to clinical trials in near real time and to generate real world evidence. Deep 6 reports real time EMR feeds across more than 30 health systems, an ecosystem of over 1,000 research facilities including 18 academic medical centers and 11 NCI designated cancer centers, and that sites find more than 25 percent more patients than with traditional recruitment; the company notes 92 percent of trial inclusion and exclusion criteria benefit from unstructured data and that 15 to 20 percent of eligible patients are found through unstructured data alone. Outputs are positioned as decision support requiring trial team validation before action. The sequencing and pharma services businesses are context, not indexed products.