Healthcare × B2B Companies
Best Healthcare AI Agencies for B2B Companies (September 2026)
Healthcare AI agencies with verified B2B client evidence — ranked by depth of documented work, then editorial quality.
Each listed agency evidences at least 2 documented B2B clients. Combined, the agencies below document 202 client engagements.
Ranked agencies for B2B clients
Rankings updated · Newest review
Top 30 of 51 agencies with documented B2B work.
Dublin, Ireland
Client evidence: 20 documented clients overall
Best for: Irish and European SMEs and founders buying a whole product build, with AI as one layer inside it rather than the whole engagement.
Modulai
#2Stockholm, Sweden
Client evidence: 12 documented clients overall
Best for: Product teams that need a model shipped into production, from clinical retrieval to real-time vision on constrained hardware.
Tallinn, Estonia
Client evidence: 10 documented clients overall
Best for: Seed-stage founders who want an LLM feature or a data-extraction pipeline built into a product by the same team that ships the app.
Tallinn, Estonia
Client evidence: 9 documented clients overall
Best for: Operators with data spread across many systems who want the pipeline and the model built and run by one team.
London, United Kingdom
Client evidence: 8 documented clients overall
Best for: Enterprises standardizing ML delivery on Google Cloud or AWS, especially where a regulator has to be satisfied.
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
#7Zurich, 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
#8London, 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.
Berlin, Germany
Client evidence: 8 documented clients overall
Best for: Enterprises putting voice or chat in front of real customers, where a wrong answer reaches the public.
Merixstudio
#10Poznań, Poland
Client evidence: 8 documented clients overall
Best for: Product owners modernizing a platform who want AI inside the delivery process and in selected features, not a model built from scratch.
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.
Tallinn, Estonia
Client evidence: 7 documented clients overall
Best for: Funded startups that need the interface and front end of an AI product designed and built while the model stays in-house.
Vstorm
#13Wrocław, Poland
Client evidence: 6 documented clients overall
Best for: Mid-market operators putting an agent inside a product or a clinical workflow, where output has to be validated before it ships.
Bismart
#14Barcelona, Spain
Client evidence: 6 documented clients overall
Best for: Organizations whose AI plans depend on fixing the data layer first, especially in healthcare, public services and tourism.
Yield Studio
#15Lyon, France
Client evidence: 6 documented clients overall
Best for: French mid-market firms adding a document-analysis or automation layer to a SaaS or internal platform they already operate.
DataSentics
#16Prague, Czech Republic
Client evidence: 5 documented clients overall
Best for: Large enterprises in finance, insurance, retail and e-commerce that need a production ML system built with a named internal data team.
Unit8
#17Lausanne, Switzerland
Client evidence: 5 documented clients overall
Best for: Industrial and financial enterprises building on Palantir Foundry, or weighing whether they should.
Visium
#18Zurich, 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.
Tooploox
#19Wrocław, Poland
Client evidence: 5 documented clients overall
Best for: Product teams needing an ML problem researched and built from scratch—no dataset, no proven approach—not an off-the-shelf integration.
Upside Lab
#20Kraków, Poland
Client evidence: 5 documented clients overall
Best for: Teams that need governed, compliant data foundations before AI—healthcare research platforms or commerce running on real customer data.
craftworks
#21Vienna, Austria
Client evidence: 5 documented clients overall
Best for: Industrial operators who need a vision or maintenance system running on their own lines and, where required, on their own infrastructure.
10Clouds
#22Warsaw, Poland
Client evidence: 5 documented clients overall
Best for: Banks, insurers and credit funds automating a defined back-office or sales workflow on a platform already run in production.
Kainos
#23Belfast, 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.
STX Next
#24Poznań, Poland
Client evidence: 5 documented clients overall
Best for: Python-heavy teams that need senior engineers now, with AI built into how the work is delivered and reviewed.
Buildo
#25Milan, Italy
Client evidence: 5 documented clients overall
Best for: Scale-ups and regulated medtech firms that need an ML or LLM feature built into an existing product by a full-stack team.
Nebuli
#26London, 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.
Madrid, Spain
Client evidence: 4 documented clients overall
Best for: Enterprises already committed to Azure that want an AI system delivered by a team with Microsoft-stack depth and named references.
Ergo
#28Dublin, 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.
Imobisoft
#29London, United Kingdom
Client evidence: 4 documented clients overall
Best for: Health and industrial companies taking a risk-scoring or compliance-reporting workflow from paper to a regulated digital platform.
2021.AI
#30Copenhagen, Denmark
Client evidence: 4 documented clients overall
Best for: Enterprises and public institutions that want a named AI system built on a governance platform with a live production record.
About this list
Healthcare B2B work—systems sold to providers, pharma and medical publishers rather than to patients—carries regulatory weight that ordinary operational AI does not, and the agencies here have documented engagements on the right side of it. Faculty's NHS AI Lab validation work sits at the regulated end of the category, and Sonrai Analytics works that end from diagnostics—computational pathology and IVD medical devices built toward EU IVDR conformity assessment with Queen's University Belfast's Precision Medicine Centre. Modulai's multi-agent retrieval system pulls clinical-trial evidence for Novo Nordisk in production. Hybrid Heroes shipped Springer Medizin's structured training app for doctors and an e-mental-health platform with Freie Universität Berlin, and appliedAI, Rewire, Lautmaler and Amsterdam Data Collective sit on a roster whose case studies skew unusually concrete.
The question that sorts this page is classification: does the documented system inform clinical decisions, or does it serve the operations around them? The first carries validation and clinical-safety obligations that reshape budgets and timelines; the second ships like ordinary enterprise software. Every candidate should be able to say immediately which side their work sat on and who signed it off—hesitation on that question, in this industry, is disqualifying.
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
51 agencies in our directory combine verified B2B client evidence with documented Healthcare work. The current top-ranked are Square Root Solutions, Modulai, Dashbouquet — 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 €20–260 per hour (median ~€65). 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 B2B 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.
2 of the agencies on this page document an embedded / team-extension working model. See the team-extension page for the full verified list, or check the engagement chips on individual profiles.