Healthcare × Public Sector
Best Healthcare AI Agencies for Public Sector (November 2026)
Healthcare AI agencies with verified public-sector client evidence — ranked by depth of documented work, then editorial quality.
Each listed agency evidences at least 2 documented public-sector clients. Combined, the agencies below document 140 client engagements.
Ranked agencies for public-sector clients
Rankings updated · Newest review
Berlin, Germany
Client evidence: 19 documented clients overall
Best for: German enterprises and federal or city administrations taking a machine-learning or LLM use case from feasibility to an operated system.
Preste
#2Paris, France
Client evidence: 17 documented clients overall
Best for: Hardware and industrial firms that need computer vision running on the device, not in the cloud, delivered as a 2–6 month build.
Madrid, Spain
Client evidence: 10 documented clients overall
Best for: Spanish utilities, public hospitals and large employers bringing a forecasting, clinical-data or Spanish-language modeling problem.
Babel
#4Madrid, Spain
Client evidence: 9 documented clients overall
Best for: Spanish and Portuguese banks, insurers and public administrations wanting AI delivered by a large integrator with the data work around it.
London, United Kingdom
Client evidence: 8 documented clients overall
Best for: Pharma, research and public-sector buyers with an NLP problem on unstructured documents that has to survive review.
Zühlke
#6Zurich, Switzerland
Client evidence: 8 documented clients overall
Best for: Regulated enterprises buying AI inside a system an engineering firm will also build, run and document.
Kortical
#7London, United Kingdom
Client evidence: 8 documented clients overall
Best for: Enterprises with a defined prediction or document-automation problem that want a model in production in weeks.
London, United Kingdom
Client evidence: 8 documented clients overall
Best for: UK enterprises, charities and public bodies already on Microsoft 365 and Azure that want Copilot adopted and governed.
Berlin, Germany
Client evidence: 7 documented clients overall
Best for: Product owners adding AI to an app that already has users, rather than starting from a model.
Mercury Labs
#10London, United Kingdom
Client evidence: 6 documented clients overall
Best for: UK public bodies and publicly funded research programs building AI tools that keep expert reviewers in charge.
Unit8
#11Lausanne, Switzerland
Client evidence: 5 documented clients overall
Best for: Industrial and financial enterprises building on Palantir Foundry, or weighing whether they should.
Visium
#12Zurich, Switzerland
Client evidence: 5 documented clients overall
Best for: Pharma and life-sciences teams that need the method described in full when the client name cannot be.
Kainos
#13Belfast, United Kingdom
Client evidence: 5 documented clients overall
Best for: UK public bodies and regulated enterprises buying delivery at program scale, with AI as one workstream inside a larger build.
Nebuli
#14London, United Kingdom
Client evidence: 5 documented clients overall
Best for: Organizations wanting a private, self-hosted generative AI workspace over their own documents rather than a public LLM.
Ergo
#15Dublin, Ireland
Client evidence: 4 documented clients overall
Best for: Irish public institutions and regulated financial firms adding AI to a Microsoft estate they already run.
Copenhagen, Denmark
Client evidence: 4 documented clients overall
Best for: Large public-sector and regulated organizations that want AI work grounded in named policy and delivery consultants.
Belfast, United Kingdom
Client evidence: 4 documented clients overall
Best for: Public bodies and research organizations that need messy data unified and throughput measured before any model work starts.
Civitta
#18Vilnius, Lithuania
Client evidence: 3 documented clients overall
Best for: Public agencies and donor-funded programs that need an AI system designed, procured and delivered inside EU rules.
Berlin, Germany
Client evidence: 3 documented clients overall
Best for: Research institutes and public bodies with a hard technical problem and a named specialist to answer for it.
Lausanne, Switzerland
Client evidence: 2 documented clients overall
Best for: Swiss institutions adding AI inside a larger systems program run by a long-established integrator.
Head-to-head
About this list
Health AI bought by or for public institutions carries a validation burden most commercial AI never meets, and the strongest agencies here have worked inside it. Dr. Mark Wernsdorfer's AMPEL system runs clinical decision support for laboratory diagnostics across more than 1,500 beds at University Hospital Leipzig—deployed clinical AI in a public hospital, which is rare on any directory. Hybrid Heroes built the DIRECT e-mental-health platform with Freie Universität Berlin and the Swiss Red Cross. Visium's pharma library names Idorsia and describes anonymized work including pathology report abstraction at 90% faster, Zühlke's health work runs from an Alzheimer's research data platform to NHS engagements, and Unit8 and ELCA bring Swiss delivery.
The questions here are not about models. Who validated the system, against what reference standard, and what evidence package went to the ethics committee or the regulator? What happens clinically when the model is unavailable or uncertain? Suppliers who have deployed in a public hospital answer these immediately and in the sector's own vocabulary; the answer that describes architecture instead is telling you this would be their first time.
Intro by Gabor Kiss, curator · How we rank
Expert Insight
Why Healthcare experience matters
Regulatory boundary awareness—The line between a documentation aid and a medical device under MDR decides your entire compliance burden. Specialists scope products to stay on the intended side of that line deliberately; generalists cross it by accident and find out during legal review
Clinical-data reality—Real clinical text is abbreviations, negations, copy-paste artifacts, and multiple languages in one record. Models that score well on public benchmarks routinely fall apart on it. Specialists validate on your data before promising numbers
Clinician adoption—Doctors have minutes per patient and no patience for tools that add clicks. Specialists design for the workflow that exists—EHR integration, review-and-sign patterns, keyboard-speed corrections—because a technically correct tool nobody opens delivers nothing
GDPR discipline for health data—Health data is special-category data with a higher lawful-basis bar, and 'send it to a third-country API' is a decision, not a default. Specialists bring data-processing agreements, EU hosting options, and de-identification pipelines as standard equipment
Frequently asked questions
20 agencies in our directory combine verified public-sector client evidence with documented Healthcare work. The current top-ranked are Merantix Momentum, Preste, Instituto de Ingeniería del Conocimiento — ordered by depth of documented client evidence, then our editorial scoring (portfolio quality, credibility, completeness); placement is never paid.
Published rates across this page's agencies run €45–260 per hour (median ~€108). Project totals depend on scope — the rate index at /rates breaks the computed bands down by region, country and team size.
Each listed agency has at least two documented, named public-sector clients — published case studies or engagement descriptions our research actually read, with source URLs stored per client. Logo walls without published evidence carry no weight, which is what separates this list from self-declared directories.