Metadvice
AI-powered software platform for clinical decision support in chronic and cardiometabolic diseases.
Website: https://www.metadvice.com/
Cover Block
Open sources
| Field | Value |
|---|---|
| Name | Metadvice |
| Tagline | AI-powered software platform for clinical decision support in chronic and cardiometabolic diseases. |
| Headquarters | London, United Kingdom [Crunchbase] |
| Founded | 2019 [Crunchbase] |
| Stage | Seed [Crunchbase] |
| Business model | SaaS |
| Industry | Healthtech |
| Technology | AI / Machine Learning |
| Geography | Western Europe |
| Growth profile | Venture Scale |
| Founding team | Co-Founders (3+) |
| Funding label | Pre-seed |
| Total disclosed | £229,830 grant offer [UKRI Gateway to Research] |
Links
Open sources
- Website: https://www.metadvice.com/
- LinkedIn: https://www.linkedin.com/company/metadvice
What an Investor Needs First
PUBLIC Metadvice builds AI-driven clinical decision support software for chronic and cardiometabolic disease, and it merits investor attention because the company has at least some external validation from UK public grant funding, a UK public-sector procurement listing, and recent institutional recognition despite limited evidence of conventional venture financing or commercial scale [UKRI Gateway to Research, retrieved 2026] [applytosupply.digitalmarketplace.service.gov.uk, April 2024] [HIN, June 2024]. The company was founded in 2019 by André Jaun, Richard W. Barker, and Serge Umansky, according to company and profile sources, with the early story appearing to sit at the intersection of clinical decision support, scientific computing, and health-system workflow improvement rather than a consumer health application [LinkedIn, retrieved 2026] [HIN, April 2025] [Crunchbase, retrieved 2026].
The product case is straightforward on paper: Metadvice says its software combines patient records, clinical guidelines, and real-world outcomes to identify high-risk patients, support treatment selection, and personalize care, with an initial focus on diseases such as type 2 diabetes, hypertension, hypercholesterolemia, chronic kidney disease, heart failure, atrial fibrillation, and polycystic ovary syndrome [metadvice.com, retrieved 2026] [LinkedIn, retrieved 2026]. The differentiation claim rests less on a novel care setting than on joining machine-learning models with guideline-based clinical logic and deployment flexibility, since the company says the software can run as a standalone application or integrate into health-system environments including electronic medical records, while also presenting a real-world-evidence use case for pharmaceutical companies [metadvice.com, retrieved 2026] [applytosupply.digitalmarketplace.service.gov.uk, April 2024] [Swiss Biotech, retrieved 2026].
The founding bench is more substantive than the company’s public footprint first suggests. Jaun is identified as co-founder and CTO, with prior work in nuclear-fusion research at EPFL and scientific computing at KTH; Barker is a co-founder and chair with a visible profile in health innovation and academia; and Umansky brings a mix of mathematical-modeling training and investment-management experience, according to company and external profile sources [HIN, April 2025] [The Hastings Center, retrieved 2026] [Bloomberg Markets, retrieved 2026] [metadvice.com, retrieved 2026].
On financing, the public record is thin on priced rounds, and that matters. The business model is described as SaaS, but the next 12 to 18 months should be watched for harder evidence on paid deployments, procurement conversion from G-Cloud visibility, and whether early recognition, including its June 2024 HIN & SHS Innovation Challenge win, translates into repeatable commercial adoption across providers or life sciences customers [applytosupply.digitalmarketplace.service.gov.uk, April 2024] [HIN, June 2024] [Venturelab, October 2024].
Partially corroborated -- Section relies on one independently confirmed grant record and several partially corroborated profile and company-source claims; commercial traction remains only lightly evidenced in public materials.
Taxonomy Snapshot
| Axis | Value |
|---|---|
| Stage | Seed |
| Business Model | SaaS |
| Industry / Vertical | Healthtech |
| Technology Type | AI / Machine Learning |
| Geography | Western Europe |
| Growth Profile | Venture Scale |
| Founding Team | Co-Founders (3+) |
| Funding | Pre-seed |
Inside the Company
PUBLIC
Metadvice presents as an early-stage clinical decision support company with a narrow enough initial wedge to be legible and a broad enough stated ambition to matter if execution follows. Public company profiles and the company website describe a business founded in 2019, headquartered in London, developing AI-powered software for clinical decision support in chronic and cardiometabolic disease [Crunchbase] [metadvice.com, retrieved 2026].
The public record is thin on formal corporate-history detail, but the operating outline is consistent across the available company-controlled sources. Crunchbase lists the business at seed stage, while the company website frames the platform around combining patient records, clinical guidelines, and outcomes data to support clinician decisions across conditions including type 2 diabetes, hypertension, hypercholesterolemia, chronic kidney disease, heart failure, atrial fibrillation, and polycystic ovary syndrome [Crunchbase] [metadvice.com, retrieved 2026].
The few dated public milestones that can be verified suggest a company still in validation rather than scaled commercialization. In April 2024, Metadvice published a service definition for the UK G-Cloud 14 framework, which indicates the product was presented for public-sector procurement rather than proving purchase or deployment [metadvice.com, retrieved 2026]. Separately, the company website states that it won the first HIN & SHS Innovation Challenge, a claim that aligns with the website's broader positioning around NHS-adjacent clinical innovation, though the overview here keeps to company and profile sources only [metadvice.com, retrieved 2026].
Partially corroborated -- Confirmed in part by Crunchbase and the company website; chronology beyond founding year relies mainly on company-controlled materials.
Under the Hood
Core product and deployment
MIXED The product story is clearer than the commercial proof. Metadvice describes itself as an AI-driven clinical decision support platform for chronic and cardiometabolic disease, built to combine patient records, clinical guidelines, and real-world outcomes so clinicians can identify higher-risk patients, choose treatment pathways, and personalize care [LinkedIn] [metadvice.com]. Public materials describe the software as usable either as a standalone decision-support application or integrated into a health system, including an electronic medical record, which matters because workflow fit is often the gating factor in clinical software adoption [metadvice.com] [UKRI Gateway to Research].
The disease focus is relatively specific for a company at this stage. Metadvice says its initial coverage includes type 2 diabetes, hypertension, hypercholesterolemia, chronic kidney disease, heart failure, atrial fibrillation, and polycystic ovary syndrome [metadvice.com] [HIN, April 2025]. That framing suggests the company is not positioning as a general-purpose clinical AI layer, but as a decision-support product with a concentrated wedge in complex long-term conditions where guideline complexity and treatment sequencing can be difficult to manage in routine care [metadvice.com] [HIN, April 2025].
Decision support model and evidence signals
MIXED The company says the platform uses neural networks alongside clinical knowledge to prioritize high-risk patients, route them to the appropriate clinician, and personalize treatment across the patient pathway [metadvice.com]. It also presents a second commercial surface for pharmaceutical companies, where the stated value proposition is generation of real-world evidence, and external directory listings describe a "Metadvice Companion AI" product that distills treatment and outcomes data into actionable insights for clinicians and patients [metadvice-ai.com] [startup.ch] [Swiss Biotech]. Those claims are directionally coherent, but most remain company-described rather than independently validated in a published product demo, peer-reviewed outcomes paper, or named customer deployment.
There are, however, a few public signals that the product has moved beyond a concept stage. UKRI records a 12-month project with a £229,830 grant offer on a total project cost of £328,328 to develop an AI engine for high-lipid management, which supports the existence of a concrete technical workstream inside the broader platform [UKRI Gateway to Research]. Metadvice also won the HIN and SHS Innovation Challenge in June 2024, and published a G-Cloud 14 service-definition document in April 2024, which indicates the product was packaged for UK public-sector procurement, though framework presence does not by itself establish live usage at scale [HIN, June 2024] [applytosupply.digitalmarketplace.service.gov.uk, April 2024].
Claim stands unchecked -- Core product descriptions rely heavily on company materials, with partial corroboration from UKRI, HIN, and the UK G-Cloud listing.
Market Research
PUBLIC
The market matters now because chronic-disease management is one of the clearest places where health systems face rising clinical complexity and staffing pressure at the same time, which makes decision-support software an easier budget conversation than broader, less defined AI claims [HIN, April 2025] [UKRI Gateway to Research, retrieved 2026].
Public evidence does not support a clean TAM, SAM, or SOM for Metadvice itself, and there is no named third-party market report in the source set that sizes AI clinical decision support for cardiometabolic disease. The safer read is to anchor on the care domains Metadvice has chosen to target: type 2 diabetes, hypertension, hypercholesterolemia, chronic kidney disease, heart failure, atrial fibrillation, and polycystic ovary syndrome [metadvice.com, retrieved 2026]. That focus matters because these conditions are long-duration, guideline-heavy, and often comorbid, which increases the value of software that can combine records, guideline logic, and outcomes data into treatment recommendations, assuming the workflow is credible in practice [metadvice.com, retrieved 2026] [HIN, April 2025].
Demand signals in the public record are still early, but they point in a coherent direction. UK Research and Innovation backed a 12-month project for high-lipid management with a total project cost of £328,328 and a grant offer of £229,830, which is better read as validation of problem importance than proof of commercial traction [UKRI Gateway to Research, retrieved 2026]. Metadvice also appeared on the UK G-Cloud 14 framework in 2024, which indicates an intent to sell into public-sector procurement channels, although framework listing alone does not establish production deployment or repeatable revenue [applytosupply.digitalmarketplace.service.gov.uk, April 2024].
Adjacent markets are at least as relevant as the core category. Metadvice describes use cases for clinicians and health systems, but also for pharmaceutical companies seeking real-world evidence, which places the company partly in the workflow-software market and partly in the evidence-generation and patient-stratification stack used by life sciences organizations [metadvice-ai.com, retrieved 2026] [Swiss Biotech, retrieved 2026]. That adjacency can widen the buyer universe if the product performs, but it also means the company may face different sales motions, validation standards, and integration requirements across provider and pharma channels.
Regulation and macro conditions cut both ways. In the UK and Europe, procurement pathways such as G-Cloud can reduce friction for listed vendors, while the broader policy climate remains supportive of technologies that promise more personalized and efficient care delivery [applytosupply.digitalmarketplace.service.gov.uk, April 2024] [HIN, April 2025]. At the same time, any product making clinician-facing recommendations in chronic disease needs evidence, workflow fit, and trust, particularly where treatment choices are complex and long-term outcomes matter, which suggests that market adoption will likely track validation and implementation capacity more than headline AI interest [HIN, April 2025] [metadvice.com, March 2025].
| Cited market signal | Figure | Interpretation |
|---|---|---|
| UKRI project total cost for high-lipid management AI engine | £328,328 | Indicates funded development activity in a cardiometabolic use case, not company market size [UKRI Gateway to Research, retrieved 2026] |
| UKRI grant offer | £229,830 | Non-dilutive support suggests institutional interest in the problem area [UKRI Gateway to Research, retrieved 2026] |
| UKRI project duration | 12 months | Implies a defined R&D scope rather than a broad commercial rollout [UKRI Gateway to Research, retrieved 2026] |
The table is narrow because the source set is narrow. What it does show is that the strongest public numeric evidence sits around funded development in a specific chronic-care workflow, not around category-scale demand or adoption.
Partially corroborated -- Section relies on one independently verifiable public grant record, one public procurement document, and company or interview-style sources for market framing and use-case context.
Competition and Substitutes
MIXED Metadvice sits in a crowded clinical decision support field where the relevant comparison is less against generic AI tooling and more against entrenched evidence platforms such as UpToDate, plus any workflow-native system already embedded in clinician practice [LinkedIn] [metadvice.com] [Crunchbase].
| Company | Positioning | Stage / Funding | Notable Differentiator | Source |
|---|---|---|---|---|
| Metadvice | AI-driven clinical decision support for chronic and cardiometabolic disease, designed to combine patient records, clinical guidelines, and real-world outcomes for treatment selection and patient prioritization | Pre-seed label; no confirmed priced venture round disclosed in the available public record | Narrower disease focus and a stated ability to operate standalone or integrate with health systems, including electronic medical records | [LinkedIn] [metadvice.com] [UKRI Gateway to Research] |
| UpToDate Expert AI | Named competitor in clinical decision support | Not established in the provided source set | Brand recognition in clinician information workflows is the practical benchmark Metadvice appears to face | [Structured facts] |
The competitive map breaks into three layers. These products typically benefit from existing clinician habit, institutional procurement history, and trust built over years, which matters more in medicine than in most software categories because the switching cost is partly workflow friction and partly perceived clinical risk.
Second are challengers built around narrower, condition-specific intelligence. Metadvice appears to be positioning here, with an initial focus on complex chronic and cardiometabolic diseases including type 2 diabetes, hypertension, hypercholesterolemia, chronic kidney disease, heart failure, atrial fibrillation, and polycystic ovary syndrome [metadvice.com]. That scope is broad enough to matter commercially, but still specialized enough to avoid a direct feature-for-feature contest with every general clinical knowledge platform.
Third are adjacent substitutes rather than direct peers. An electronic medical record, a care pathway tool, or even a pharmacist-led protocol can satisfy part of the same job if the buyer's goal is triage, guideline adherence, or population management rather than algorithmic personalization [metadvice.com] [applytosupply.digitalmarketplace.service.gov.uk, April 2024]. That distinction matters because Metadvice is not only competing for software budget, it is also competing against incumbent process.
The company's edge, such as it can be assessed from public evidence, is specificity rather than scale. Its product claims point to a stack that combines patient records, guidelines, and real-world outcomes, and the UKRI-backed lipid-management project suggests at least one concrete attempt to build disease-specific decision support rather than a general-purpose assistant [UKRI Gateway to Research] [metadvice.com]. The HIN innovation challenge win in June 2024 adds a modest external signal that the concept resonates with health-system stakeholders, even if it does not prove production adoption [HIN, June 2024].
That edge is promising but still perishable. Disease-specific intelligence can be durable if it is built on proprietary outcome data, validated care pathways, and procurement relationships that are hard to replicate, but the available public record does not yet establish those moats independently [Swiss Biotech] [startup.ch]. The same specialization can also narrow the early go-to-market path if each indication requires separate clinical validation, workflow integration, or buyer education.
Metadvice looks most exposed where incumbents already own clinician attention. The G-Cloud 14 service-definition document helps on procurement visibility, but framework listing is not the same thing as usage, and it does not solve the distribution problem inside hospitals or physician groups [applytosupply.digitalmarketplace.service.gov.uk, April 2024].
The company is also exposed to buyers who prefer broad platforms over point solutions. Its stated audience spans clinicians, clinics, health systems, pharmaceutical companies, disease-research organizations, and patients, which reads as ambition across several customer types rather than a clearly evidenced single dominant wedge [metadvice-ai.com] [LinkedIn]. In early-stage healthtech, a wide target list can be an asset for experimentation, but it can also blur product requirements and slow sales motion if one channel has not clearly emerged.
The most plausible 18-month competitive scenario is bifurcated by proof of deployment. Winner if X: Metadvice, if it can convert its disease-specific positioning, UK public-sector procurement visibility, and non-dilutive R&D support into named clinical deployments with measurable workflow or outcomes evidence [UKRI Gateway to Research] [applytosupply.digitalmarketplace.service.gov.uk, April 2024]. On the current evidence, this is a contest where distribution and validation likely matter more than model architecture.
Opportunity
PUBLIC The prize here is not a better clinical dashboard, it is a chance to become a decision layer that sits between raw patient data and high-stakes treatment choices in chronic disease, where small workflow wins can compound across very large care populations [metadvice.com, retrieved 2026] [HIN, April 2025].
The headline opportunity is straightforward. If Metadvice can move from pilot-style visibility to repeatable deployment, it could become a clinical decision-support platform for cardiometabolic and other chronic conditions where care pathways are complex, longitudinal, and expensive to manage [metadvice.com, retrieved 2026] [UKRI Gateway to Research]. The evidence for reachability is still early, but it is not purely aspirational: the company has defined a product that combines patient records, clinical guidelines, and real-world outcomes, has positioned the software to work either standalone or inside existing health systems, and has already been visible enough to win the HIN & SHS Innovation Challenge in June 2024 and to publish a G-Cloud 14 service definition for UK public-sector procurement [LinkedIn, retrieved 2026] [metadvice.com, retrieved 2026] [HIN, June 2024] [applytosupply.digitalmarketplace.service.gov.uk, April 2024]. In healthcare software, those signals do not prove commercial scale, but they do suggest that the company is trying to solve a real integration and procurement problem rather than building only for demo environments [applytosupply.digitalmarketplace.service.gov.uk, April 2024] [UKRI Gateway to Research].
The upside paths are best understood as a small number of concrete scaling motions rather than one generic "AI in healthcare" bet.
| Scenario | What happens | Catalyst | Why it's plausible |
|---|---|---|---|
| NHS workflow foothold | Metadvice becomes a decision-support layer used by UK care providers for chronic-disease triage and treatment guidance | Conversion from framework visibility and challenge recognition into paid NHS or public-sector deployments | The company published a G-Cloud 14 service definition in 2024, which at minimum shows procurement readiness, and it won the HIN & SHS Innovation Challenge in 2024, which suggests institutional relevance in the UK health system [applytosupply.digitalmarketplace.service.gov.uk, April 2024] [HIN, June 2024] |
| Pharma evidence engine | The platform becomes a recurring software and evidence partner for pharmaceutical companies running chronic-disease programs | A named pharma collaboration or evidence-generation program using the companys treatment and outcomes data layer | Metadvice publicly states that pharmaceutical companies are a target customer and that its value proposition includes generating real-world evidence; Venturelab also described its use of treatment and outcome data in personalized care [metadvice-ai.com] [Venturelab, October 2024] |
| Cross-border specialist platform | Metadvice turns early UK and Swiss visibility into a broader European specialist platform for cardiometabolic care pathways | One validated hospital or research deployment that can be referenced across health systems with similar chronic-disease pressures | HIN reported collaboration involving Innosuisse and Inselspital, while Venturelab selected the company for a Swiss National Medtech Team roadshow to Boston, indicating some cross-border institutional support and external validation [HIN, March 2026] [Venturelab, October 2024] |
What compounding looks like is a data and workflow flywheel, but only if deployment quality proves out. Metadvice says its software combines patient records, guidelines, and real-world outcomes, and separate company-facing materials say it sources data from a growing global network of practitioners and can assist pharmaceutical companies with real-world evidence generation [metadvice.com, retrieved 2026] [Swiss Biotech, retrieved 2026] [startup.ch]. If even a modest number of provider deployments produce credible treatment-pathway and outcomes insights, the product could become more clinically useful, more defensible in procurement, and more valuable to biopharma partners looking for disease-specific evidence tools [metadvice-ai.com] [Venturelab, October 2024].
The reason this can compound faster than a typical point solution is that chronic and cardiometabolic disease management is recurrent rather than episodic. A system that helps identify high-risk patients, route them to appropriate clinicians, and tailor treatment decisions can, in principle, attach to repeated visits, medication adjustments, and longitudinal monitoring rather than a single diagnostic moment [metadvice.com, retrieved 2026] [HIN, April 2025]. The companys initial disease focus, type 2 diabetes, hypertension, hypercholesterolemia, chronic kidney disease, heart failure, atrial fibrillation, and polycystic ovary syndrome, is broad enough that one successful deployment could create adjacency into multiple care pathways without a full go-to-market reset each time [metadvice.com, retrieved 2026].
The size of the win is hard to state precisely because the public record here does not include confirmed revenue, customer count, or market-sizing data, and there is no cited public comparable in the source set that would support a clean valuation bridge. The more careful framing is this: if Metadvice were to establish itself as a trusted workflow and evidence layer across UK and European chronic-disease programs, it could plausibly become an asset of strategic value to larger healthtech, clinical-software, or life-sciences data platforms (scenario, not a forecast) [applytosupply.digitalmarketplace.service.gov.uk, April 2024] [Venturelab, October 2024]. The public evidence supports a real problem area, a technically ambitious product, and early institutional validation; it does not yet support a quantified upside case, which is why the opportunity is meaningful but still conditional.
Partially corroborated -- The section relies on one independently verifiable grant record and procurement evidence, plus institutional profile coverage and company materials for product scope and customer ambitions.
Sources
Open sources
[UKRI Gateway to Research, retrieved 2026] UKRI Gateway to Research, project record | https://gtr.ukri.org/projects?ref=52685
[applytosupply.digitalmarketplace.service.gov.uk, April 2024] G-Cloud 14 Service Definition Document | https://assets.applytosupply.digitalmarketplace.service.gov.uk/g-cloud-14/documents/719829/389858029905361-service-definition-document-2024-04-30-1100.pdf
[HIN, June 2024] HIN & SHS Innovation Challenge | https://www.hin.ch/en/innovation-challenge
[LinkedIn, retrieved 2026] Metadvice | LinkedIn | https://www.linkedin.com/company/metadvice
[HIN, April 2025] Massgeschneiderte Medizin dank KI: Die Lösung von Metadvice. | https://www.hin.ch/de/blog/2024/massgeschneiderte-medizin-dank.cfm
[Crunchbase, retrieved 2026] Metadvice - Crunchbase Company Profile & Funding | https://www.crunchbase.com/organization/metadvice
[metadvice.com, retrieved 2026] Metadvice - Clinical Decision Intelligence | https://www.metadvice.com/
[The Hastings Center, retrieved 2026] Richard Barker, OBE | The Hastings Center | https://www.thehastingscenter.org/who-we-are/people/richard-barker/
[Bloomberg Markets, retrieved 2026] Serge Umansky, Signet Capital Management Ltd: Profile and Biography - Bloomberg Markets | https://www.bloomberg.com/profile/person/4409735
[Venturelab, October 2024] Metadvice: The Venture Leader Medtech accelerating personalised and complex disease care | https://www.venturelab.swiss/Metadvice-The-Venture-Leader-Medtech-accelerating-personalised-and-complex-disease-care
[Swiss Biotech, retrieved 2026] Metadvice (Suisse) SA - Swiss Biotech | https://www.swissbiotech.org/listing/metadvice-suisse-sa/
[startup.ch, retrieved 2026] Metadvice Suisse SA | startup.ch | https://www.startup.ch/index.cfm?page=110&lid=1&cid=126650
[metadvice.com, March 2025] Metadvice article on emerging technologies and pharmacotherapy choices | https://www.metadvice.com/
[LinkedIn] Metadvice | LinkedIn | https://www.linkedin.com/company/metadvice
[metadvice.com] Metadvice - Clinical Decision Intelligence | https://www.metadvice.com/
[UKRI Gateway to Research] UKRI Gateway to Research, project record | https://gtr.ukri.org/projects?ref=52685
[Crunchbase] Metadvice - Crunchbase Company Profile & Funding | https://www.crunchbase.com/organization/metadvice
[startup.ch] Metadvice Suisse SA | startup.ch | https://www.startup.ch/index.cfm?page=110&lid=1&cid=126650
[Swiss Biotech] Metadvice (Suisse) SA - Swiss Biotech | https://www.swissbiotech.org/listing/metadvice-suisse-sa/
[metadvice-ai.com] Metadvice Collaborate | https://metadvice-ai.com/company/collaborate/
[LinkedIn, Dr Jonathan Serjeant, retrieved 2026] Dr Jonathan Serjeant | LinkedIn | https://www.linkedin.com/in/jonathan-serjeant/
[HIN, March 2026] Médecine sur mesure grâce à l’IA: la solution de Metadvice. | https://www.hin.ch/fr/blog/2024/medecine-sur-mesure-grace-ia-l.cfm
Articles about Metadvice
- Metadvice's AI Engine for Lipid Management Wins a £230,000 UK Grant — The London-based startup is building a clinical decision support platform for complex chronic conditions, backed by a non-dilutive grant and a team spanning medicine, finance, and physics.