OM1
AI-powered real-world data and analytics for healthcare outcomes, research, and clinical decision-making.
Website: https://www.om1.com/
Cover Block
Publicly reported
| Field | Value |
|---|---|
| Company | OM1 |
| Tagline | AI-powered real-world data and analytics for healthcare outcomes, research, and clinical decision-making |
| Headquarters | Boston, United States [Crunchbase] |
| Founded | 2015 [Crunchbase] |
| Stage | Series D+ [Crunchbase] |
| Business model | B2B |
| Industry | Healthtech |
| Technology | AI / Machine Learning |
| Geography | North America |
| Growth profile | Venture Scale |
| Founding team | Repeat Founder |
| Funding label | $100M+ |
| Total disclosed funding | Approximately $176,000,000 [MedCity News, July 2021] |
Links
Publicly reported
- Website: https://www.om1.com/
Summary and Signal
PUBLIC OM1 builds AI-enabled real-world data infrastructure for healthcare research and clinical decision-making, and it merits investor attention because it sits at the intersection of two durable budgets: life sciences demand for longitudinal outcomes data and provider demand for tools that can translate messy clinical records into usable evidence [MedCity News, July 2021] [TechCrunch, December 2019]. Founded in Boston in 2015, the company was started by Richard Gliklich, who previously founded Outcome Sciences, a real-world research company acquired by Quintiles in 2011, which gives OM1 a more credible origin story than is typical for healthcare data startups [OM1] [Business Wire, October 2011].
The core offer is a data-and-analytics platform that gathers and standardizes information from sources including electronic health records, laboratories, claims, and patient inputs, then applies predictive models across chronic disease use cases such as real-world evidence, patient identification, and clinical decision support [MedCity News, July 2021] [MobiHealthNews, May 2018] [healthydata.science]. Public materials suggest the differentiation rests less on a single application layer and more on the combination of disease-specific longitudinal datasets, networked data ingestion, and model development, a strategy the company began commercializing with its first dataset and AI model in 2017 according to reported coverage [TechCrunch, December 2019] [Healthcare Innovation, April 2017].
Leadership depth is central to the pitch. Gliklich is identified as founder and CEO by the company and third-party org charts, while Dan Levy is listed as Chief Data Officer, which indicates continuity between clinical domain expertise and data platform execution even if public evidence on the broader bench remains limited [OM1] [The Org]. On capital formation, OM1 has raised four disclosed rounds: $15 million Series A in 2017, $21 million Series B in 2018, $50 million Series C in 2019, and an $85 million Series D financing in 2021, with backing from General Catalyst, Polaris Partners, Scale Venture Partners, D1 Capital Partners, Kaiser Permanente, and Breyer Capital [Healthcare Innovation, April 2017] [MobiHealthNews, May 2018] [TechCrunch, December 2019] [MedCity News, July 2021].
The business model appears firmly B2B, selling data, analytics, and related solutions into life sciences, providers, payers, regulators, and medical societies, though public sources do not provide enough contract detail to judge revenue mix or concentration [MedCity News, July 2021] [TechCrunch, December 2019]. Over the next 12 to 18 months, the main issues to watch are whether OM1 can translate its expanding model claims, including the newer PhenOM validation announcement, into independently visible commercial adoption, and whether strategic partnerships such as the Panalgo collaboration deepen distribution rather than remain point integrations [Business Wire, November 2026] [OM1].
One source, partially checked -- Relies primarily on named publisher funding coverage and company materials, with partial corroboration on team and product positioning.
Taxonomy Snapshot
| Axis | Value |
|---|---|
| Stage | Series D+ |
| Business Model | B2B |
| Industry / Vertical | Healthtech |
| Technology Type | AI / Machine Learning |
| Geography | North America |
| Growth Profile | Venture Scale |
| Founding Team | Repeat Founder |
| Funding | $100M+ total disclosed, approximately $171M from confirmed rounds |
Company Overview
PUBLIC
OM1 presents as a Boston-based healthcare data and artificial intelligence company formed in 2015, with a business built around real-world clinical data and analytics for outcomes research and care decisions [Crunchbase] [OM1]. Public company materials identify Richard Gliklich, MD as founder, and Crunchbase places the company in Boston with a venture-backed profile that aligns with the disclosed financing history [OM1] [Crunchbase].
The chronology that is cleanly supported by company and database sources is straightforward. OM1 was founded in 2015 [Crunchbase] [OM1]. Its funding record on Crunchbase tracks a Series A in April 2017, a Series B in May 2018, a Series C in December 2019, and an $85 million Series D financing in July 2021, which matches the company’s own financing narrative across public materials [Crunchbase] [OM1]. That sequence matters because it shows a company that moved from formation into repeated institutional fundraising within two years, then continued to raise through later-stage rounds without any public indication in the provided sources of an exit or public listing [Crunchbase] [OM1].
The operating story today is broader than a single product line. OM1’s website describes a platform spanning AI-ready real-world data, analytics products including Orion, Lyra, and Polaris, and registry support services through its Registry Center of Excellence [OM1]. On public evidence alone, the throughline is consistent: the company started with a longitudinal data and outcomes focus and has since expanded its public positioning toward a wider clinical intelligence stack for life sciences and healthcare stakeholders [OM1].
Well sourced -- Confirmed by Crunchbase and OM1.
The Product and the Stack
Public record plus analysis
OM1’s product surface is clearest when read from the data layer upward. Public reporting and company materials describe a platform that gathers, standardizes, enriches, and analyzes clinical information from electronic health records, laboratory sources, claims, patient inputs, and unstructured clinical notes to support real-world evidence, outcome measurement, patient identification, clinical decision-making, and treatment personalization [MedCity News, July 2021] [OM1] [healthydata.science]. The company publicly names three products, OM1 Orion, OM1 Lyra, and OM1 Polaris, and also describes a Registry Center of Excellence that provides consultation, scientific oversight, and data-quality support for registry programs [OM1, May 2024] [OM1].
The technical bet appears to rest on pairing disease-specific longitudinal data assets with predictive modeling, rather than selling workflow software alone. Trade coverage from 2019 and 2021 described OM1 as building clinical data networks and AI models for chronic disease use cases, while the company’s more recent public materials position PhenOM as a healthcare foundation model trained and validated on more than 400 million de-identified patient records and used to generate predictions across more than 1,700 clinical outcomes [TechCrunch, December 2019] [MedCity News, July 2021] [Business Wire, November 2026]. Those model-scale claims are company-announced and should be read that way, but they are directionally consistent with OM1’s long-stated focus on combining normalized real-world data with outcome prediction [Business Wire, November 2026] [Healthcare Innovation, April 2017].
The commercial edge, on the public record, is less about a disclosed model architecture than about data preparation and domain packaging. OM1 says its datasets are HIPAA-compliant, de-identified, and AI-ready, and external coverage points to productized data-network automation plus disease-focused applications in areas such as dermatology, rheumatology, cardiology, gastroenterology, respiratory disease, neurosciences, and behavioral health [OM1] [MedCity News, July 2021]. There are also public signals of ecosystem distribution, including a 2024 partnership expansion with Panalgo around OM1’s PremiOM datasets, and a dermatology project that paired the American Academy of Dermatology’s DataDerm with OM1 Patient Finder, although those references do not disclose usage depth or economic terms [OM1] [Owler Company Profile] [YesPress].
No independent source found -- This section combines independent press coverage with multiple material product and model claims that are company-only or lightly corroborated by secondary references.
The Market They Are Entering
PUBLIC
This market matters now because buyers across healthcare and life sciences are under pressure to extract decision-grade evidence from routine clinical data, while advances in model development have made larger longitudinal datasets more commercially relevant [MedCity News, July 2021] [TechCrunch, December 2019].
Public evidence here is thinner on formal market sizing than on demand direction. No named third-party TAM figure was captured for OM1’s exact market, so the analysis has to stay close to the observable use cases in the record: real-world evidence, clinical outcomes analytics, patient identification, and AI models built on longitudinal healthcare data [MobiHealthNews, May 2018] [MedCity News, July 2021]. Those use cases sit at the intersection of healthcare analytics software and real-world data services, with OM1 positioned around chronic disease datasets and predictive modeling rather than a single workflow tool [TechCrunch, December 2019] [OM1].
Demand drivers are relatively clear. Trade coverage consistently describes OM1 selling into a set of buyers that includes pharmaceutical companies, providers, payers, regulators, and medical societies, which suggests demand is coming from repeated needs to measure treatment effectiveness, compare outcomes, support research, and find patients for studies or interventions [TechCrunch, December 2019] [MedCity News, July 2021] [MobiHealthNews, May 2018]. The company’s 2021 financing coverage also points to continued investment in clinical data networks that automate intake from EHRs, laboratories, and patients, which is a useful indicator that the commercial bottleneck is not only model performance but also access to normalized longitudinal data at scale [MedCity News, July 2021].
The adjacent markets are broad enough to matter for strategy. OM1 can be read as participating partly in real-world evidence infrastructure, partly in provider and payer analytics, and partly in clinical AI enablement, especially where de-identified records are used to train or validate predictive systems [OM1] [Business Wire, November 2026]. That overlap cuts both ways: it expands the reachable budget pool, but it also means substitution risk can come from data vendors, analytics platforms, registry specialists, and in-house life sciences evidence teams rather than from one neatly bounded category [TechCrunch, December 2019] [OM1].
Regulation and macro conditions are supportive in principle, though the public record here is still more directional than quantified. Healthcare buyers continue to favor evidence generation that can use existing care data, especially where randomized trials are costly or too narrow for post-market questions, and OM1’s positioning around de-identified, HIPAA-compliant datasets fits that purchasing logic according to company materials [OM1]. At the same time, the market remains shaped by privacy constraints, data-use governance, and the practical difficulty of turning fragmented clinical records into analysis-ready assets, which is why companies in this segment tend to compete as much on data curation and scientific credibility as on software features [MedCity News, July 2021] [TechCrunch, December 2019].
| Market lens | What public sources support | Evidence quality |
|---|---|---|
| Core market | Real-world data and outcomes analytics for healthcare and life sciences buyers [MobiHealthNews, May 2018] [TechCrunch, December 2019] | Moderate |
| Buyer segments | Providers, payers, pharmaceutical companies, regulators, and medical societies [MedCity News, July 2021] [OM1] | Mixed |
| Growth tailwind | Increased value of longitudinal clinical data networks feeding analytics and AI models [MedCity News, July 2021] [Business Wire, November 2026] | Mixed |
| Adjacent markets | Registry services, patient identification, clinical decision support, and AI model training on healthcare data [OM1] [TechCrunch, December 2019] | Mixed |
The table shows a market story with clear demand contours but limited third-party sizing in the available record. For investors, that usually means the diligence burden shifts from top-down TAM slides to bottom-up proof that OM1 can win budget within specific evidence and analytics workflows.
One source, partially checked -- Section relies on named trade publications for buyer categories and demand drivers, but lacks independent third-party market sizing and uses some company-sourced positioning.
The Competitive Field
Positioning
MIXED OM1 appears best understood as a real-world data and clinical AI platform sitting between traditional outcomes research vendors, registry operators, and newer model-driven decision support companies, with its position defined more by depth of longitudinal healthcare data than by a consumer-facing application layer [MedCity News, July 2021] [TechCrunch, December 2019] [OM1].
The segment map matters because OM1 is competing across several buying centers at once. In life sciences and medical research, the closest alternatives are real-world evidence and analytics platforms that help sponsors evaluate treatment effectiveness, safety, and patient cohorts, a lane OM1 has pursued since at least its 2017 and 2018 financings [Healthcare Innovation, April 2017] [MobiHealthNews, May 2018]. In provider and medical society workflows, the substitute set is broader: registry software, internal analytics teams, and disease-specific data programs can all address parts of the same need, particularly outcome measurement and patient identification [OM1] [PMWC Precision Medicine World Conference, 2026]. In clinical AI, the adjacent field includes companies trying to build predictive or generative models on healthcare data, but OM1's own public case rests on the combination of de-identified longitudinal records, disease-specific normalization, and research-grade evidence generation rather than on a general-purpose model claim alone [Business Wire, November 2026] [MedCity News, July 2021].
OM1's clearest edge today is data compounding, not branding. The company says its PhenOM model was trained and validated on more than 400 million de-identified patient records and can generate predictions across more than 1,700 clinical outcomes, while its product set spans data assets, patient finding, and analytics tools such as Orion, Lyra, and Polaris [Business Wire, November 2026] [OM1, May 2024]. If those company-stated figures hold up in customer use, that creates a practical moat through training data, workflow familiarity, and disease-specific tuning; if they do not translate into better decisions or easier regulatory-grade studies, the edge becomes perishable because larger data owners and established evidence platforms can narrow feature gaps with distribution and existing customer trust [OM1] [TechCrunch, December 2019].
The exposure is straightforward. OM1 does not appear, from the public record provided here, to own a dominant care delivery channel, payer channel, or embedded EHR surface, which leaves it vulnerable to adjacent players with direct system access or entrenched analytics distribution [MedCity News, July 2021]. Panalgo is one named example from the source set, not as a declared head-to-head rival but as a platform with enough overlap in analytics workflow to matter; the June 2024 partnership suggests OM1 saw value in meeting users inside another analytics environment rather than displacing it outright [OM1] [Owler Company Profile]. That is commercially sensible, but it also implies that some downstream user attention may be controlled by partners rather than captured natively by OM1.
The most plausible 18-month scenario is a sorting between companies that can prove workflow utility and those that remain primarily data suppliers. OM1 is a plausible winner if buyers continue to prefer integrated datasets plus prediction tooling for real-world evidence, particularly in chronic disease areas where longitudinal context matters and where the founder's prior outcomes-research track record still carries weight [Business Wire, October 2011] [Healthcare Innovation, April 2017]. Panalgo is a plausible winner if the market tilts toward neutral analytics operating layers that aggregate many data sources, because that model can reduce dependence on any single dataset vendor [Owler Company Profile]. The more exposed position, conditional on that shift, would be any vendor whose differentiation rests mainly on proprietary data claims without durable workflow control, and OM1 would need its product surfaces, not only its data scale, to carry more of the account.
One source, partially checked -- Core company positioning and funding history are corroborated by trade coverage and company materials, but competitor naming in the provided source set is sparse and one overlap reference relies on partnership evidence rather than direct competitive reporting.
Opportunity
PUBLIC
If OM1 executes, the prize is not a niche analytics business but a position in the clinical data stack where life sciences companies, providers, payers, and medical societies rely on one platform for real-world evidence generation and outcome prediction across chronic disease workflows [MedCity News, July 2021] [TechCrunch, December 2019].
The headline opportunity is to become a scaled infrastructure layer for longitudinal real-world data and clinical AI in healthcare outcomes. That is reachable, rather than merely aspirational, because OM1 has spent nearly a decade assembling the ingredients that are difficult to reproduce quickly: disease-specific data networks, a track record of raising large private rounds, and an operating model aimed at multiple budget holders rather than a single buyer class [Healthcare Innovation, April 2017] [MobiHealthNews, May 2018] [TechCrunch, December 2019] [MedCity News, July 2021]. The public record also shows product breadth across patient identification, prediction, and evidence generation, which matters because healthcare data businesses tend to compound when one dataset can support several adjacent use cases [OM1] [MedCity News, July 2021].
A second reason the upside is credible is founder-market fit. Richard Gliklich previously founded Outcome Sciences, which was acquired by Quintiles in 2011, and later moved into a global late-phase leadership role there, giving OM1 a founder with direct experience in outcomes research, registries, and commercializing evidence infrastructure for industry customers [Business Wire, October 2011] [Healthcare Innovation, April 2017]. In this part of healthtech, repeat-founder pattern recognition often matters more than surface-level product novelty, because sales cycles, data rights, and scientific credibility are the real gating factors.
| Scenario | What happens | Catalyst | Why it's plausible |
|---|---|---|---|
| Multi-indication evidence utility | OM1 becomes a standard external data and analytics partner for pharma and medtech programs across several chronic disease areas | Continued expansion of disease coverage and product packaging such as Orion, Lyra, and Polaris, plus partnerships around datasets and analytics distribution [OM1, May 2024] [OM1] | Public sources already place OM1 across dermatology, rheumatology, cardiology, gastroenterology, respiratory disease, neurosciences, and behavioral health, with products used for real-world evidence and patient identification [OM1] [MedCity News, July 2021] |
| Registry and society infrastructure layer | OM1 becomes the preferred technology and analytics backbone for medical societies and registry operators seeking longitudinal outcomes measurement | Programs like the American Academy of Dermatology project combining DataDerm with OM1 Patient Finder, and OM1's registry consulting capability [YesPress] [OM1] | The company has a stated Registry Center of Excellence and public evidence of society-linked data work, which suggests credibility in a segment where trust and scientific process matter as much as software features [OM1] [YesPress] |
| Foundation model distribution into research workflows | OM1's large-scale de-identified data assets and PhenOM model become embedded in clinical research and decision-support workflows | Validation publicity around PhenOM and channel partnerships such as Panalgo's IHD Analytics Platform [Business Wire, November 2026] [OM1] | OM1 says PhenOM was trained and validated on more than 400 million de-identified patient records and more than 1,700 clinical outcomes, while the Panalgo partnership points to a route into existing analytics environments rather than requiring greenfield adoption [Business Wire, November 2026] [OM1] |
The scenarios point to the same underlying compounding logic. Each new disease network, registry program, or analytics partnership can enlarge the utility of the data layer, which in turn supports more prediction products, more evidence studies, and more reasons for customers to stay inside the same ecosystem [MedCity News, July 2021] [OM1]. That is not a consumer-style network effect, but it can still be powerful: normalized longitudinal data gets more valuable when paired with repeatable model validation, domain-specific workflows, and established scientific relationships.
There are early public signs that this flywheel may already be forming. OM1 has disclosed a multi-product lineup, it has partnered with Panalgo on dataset availability inside an analytics platform, and it continues to market both data assets and model-driven applications rather than a single point tool [OM1, May 2024] [OM1]. The 2026 PhenOM validation announcement, while company-promoted and therefore best treated cautiously, also shows management trying to convert a proprietary data estate into a reusable model layer rather than selling one-off services alone [Business Wire, November 2026].
The size of the win is harder to quantify cleanly because the source set here does not include a public peer market cap or a named TAM study that can be cited directly. Even so, the outline of the upside is visible. If the "foundation model distribution into research workflows" scenario plays out, OM1 could plausibly mature into a strategic data-and-analytics asset for CROs, life sciences software platforms, or evidence-generation incumbents that need proprietary longitudinal data plus validated prediction capability at scale (scenario, not a forecast) [Business Wire, November 2026] [Business Wire, October 2011]. If instead the company wins the registry and society infrastructure path, the value would likely come from becoming embedded in slow-moving but durable institutional workflows where replacement is costly and expansion can happen indication by indication (scenario, not a forecast) [OM1] [YesPress].
No independent source found -- This section relies on a mix of independent funding coverage and company-linked product, partnership, and model-performance claims, with several material upside premises supported primarily by OM1 or press-release distribution.
Sources
Publicly reported
[Crunchbase] OM1 | https://www.crunchbase.com/organization/om1
[MedCity News, July 2021] OM1 gains $85M to expand clinical data networks, AI models | https://medcitynews.com/2021/07/om1-gains-85m-to-expand-clinical-data-networks-ai-models/
[TechCrunch, December 2019] Applying big data analytics to patient records, OM1 offers insights to hospitals and pharma | https://techcrunch.com/2019/12/17/applying-big-data-analytics-to-patient-records-om1-offers-insights-to-hospitals-and-pharma/
[OM1] OM1 | https://www.om1.com/
[Business Wire, October 2011] Quintiles Announces Acquisition of Outcome Sciences | https://www.businesswire.com/news/home/20111003005691/en/Quintiles-Announces-Acquisition-of-Outcome-Sciences
[MobiHealthNews, May 2018] Health outcomes AI company OM1 lands $21M in Series B funding | https://www.mobihealthnews.com/news/health-outcomes-ai-company-om1-lands-21m-series-b-funding
[healthydata.science] OM1 | https://healthydata.science/
[The Org] Richard Gliklich | https://theorg.com/org/om1/org-chart/richard-gliklich
[Healthcare Innovation, April 2017] Healthcare Analytics Startup OM1 Raises $15M | https://www.hcinnovationgroup.com/analytics-ai/news/13028407/healthcare-analytics-startup-om1-raises-15m
[Business Wire, November 2026] OM1 Publishes Validation Results from a Single Healthcare Foundation Model Across More than 1700 Predicted Clinical Outcomes | https://www.businesswire.com/news/home/20261102423771/en/OM1-Publishes-Validation-Results-from-a-Single-Healthcare-Foundation-Model-Across-More-than-1700-Predicted-Clinical-Outcomes
[Owler Company Profile] OM1 Company Profile | https://www.owler.com/company/om1
[YesPress] AAD and OM1 launch project combining DataDerm and Patient Finder | https://yespress.com/
[PMWC Precision Medicine World Conference, 2026] Rich Gliklich - 2026sv - PMWC Precision Medicine World Conference | https://pmwcintl.com/speaker/rich-gliklich-256_om1_2026sv/
[OM1, May 2024] OM1 | https://www.om1.com/
Articles about OM1
- OM1's Foundation Model Predicts More Than 1,700 Clinical Outcomes — The Boston-based company, founded by a physician who sold his last venture to Quintiles, is using its massive dataset to answer questions regulators and drugmakers have long struggled with.