Top Healthcare AI Agencies in Europe

Best for: German enterprises and federal or city administrations taking a machine-learning or LLM use case from feasibility to an operated system.

Best for: Enterprises standardizing ML delivery on Google Cloud or AWS, especially where a regulator has to be satisfied.

Best for: Large enterprises in finance, insurance, retail and e-commerce that need a production ML system built with a named internal data team.

Best for: Industrial and financial enterprises building on Palantir Foundry, or weighing whether they should.

Best for: Enterprises and public bodies that need AI deployed under regulatory or safety scrutiny.

Best for: Mid-market operators putting an agent inside a product or a clinical workflow, where output has to be validated before it ships.

Best for: Regulated German industrial and mid-market firms that want the model running inside their own Azure or AWS tenant.

Best for: Pharma and life-sciences teams that need the method described in full when the client name cannot be.

Best for: Pharma, research and public-sector buyers with an NLP problem on unstructured documents that has to survive review.

Best for: Enterprises already committed to Azure that want an AI system delivered by a team with Microsoft-stack depth and named references.

Best for: Enterprises running an AI program who want their own team able to continue it afterwards.

Best for: Spanish utilities, public hospitals and large employers bringing a forecasting, clinical-data or Spanish-language modeling problem.

Best for: Irish public institutions and regulated financial firms adding AI to a Microsoft estate they already run.

Best for: Regulated enterprises buying AI inside a system an engineering firm will also build, run and document.

Best for: Regulated organizations whose AI program has to satisfy a supervisor, an auditor or a board risk committee.

Best for: Industrial enterprises running an AI program that has to satisfy governance as well as engineering.

Best for: Early-stage product companies that need the ML core of their product built, tested and handed over with the IP.

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.

Best for: Product teams needing an ML problem researched and built from scratch—no dataset, no proven approach—not an off-the-shelf integration.

Software Mind is a Kraków-headquartered software company founded in 1999, offering generative AI development alongside cloud and modernization services. It builds its own agent-based tooling for large-scale migration work.

Best for: Public agencies and donor-funded programs that need an AI system designed, procured and delivered inside EU rules.

Best for: Teams that need governed, compliant data foundations before AI—healthcare research platforms or commerce running on real customer data.

Best for: Enterprises with a defined prediction or document-automation problem that want a model in production in weeks.

deepsense.ai is a Warsaw machine-learning consultancy building production AI, language-model, computer-vision and MLOps systems for enterprise clients.

Best for: Health and industrial companies taking a risk-scoring or compliance-reporting workflow from paper to a regulated digital platform.

Best for: Operators with data spread across many systems who want the pipeline and the model built and run by one team.

Best for: Enterprises and public institutions that want a named AI system built on a governance platform with a live production record.

Best for: Manufacturers automating one inspection station or technical-document search on an existing line, not buying an open-ended AI program.

Lingaro is a Warsaw-headquartered data and AI engineering firm building enterprise data platforms, analytics and generative AI for global consumer brands.

Best for: Pharmaceutical companies and statutory health insurers that need analysis to survive a regulatory review and the code to come with it.

Best for: Operations teams that want automation bought against a payback number, especially in healthcare revenue cycle.

Best for: Industrial operators who need a vision or maintenance system running on their own lines and, where required, on their own infrastructure.

Best for: Large French consumer businesses industrializing scoring or support automation that already runs past the pilot stage.

Best for: Banks, insurers and credit funds automating a defined back-office or sales workflow on a platform already run in production.

Best for: Large public-sector and regulated organizations that want AI work grounded in named policy and delivery consultants.

Best for: Enterprises putting voice or chat in front of real customers, where a wrong answer reaches the public.

Best for: Product teams that need a model shipped into production, from clinical retrieval to real-time vision on constrained hardware.

Best for: Regulated institutions and retailers with a pricing, risk or monitoring problem that can be measured.

Best for: Product teams with a defined forecasting, fraud or analytics problem who want an established ML team on fixed-price or dedicated terms.

Best for: Nordic marketing and sales teams that want AI tools built into HubSpot, Teams or Microsoft 365 and their own staff trained to run them.

Best for: Teams that want the senior consultant doing the build, with the architecture and its limits written down before delivery.

Tensorway is an Alicante AI development firm founded in 2019, building AI agents, machine-learning models and document-processing systems for legal, financial and software clients.

Best for: UK public bodies and regulated enterprises buying delivery at program scale, with AI as one workstream inside a larger build.

Best for: Research institutes and public bodies with a hard technical problem and a named specialist to answer for it.

Best for: UK enterprises, charities and public bodies already on Microsoft 365 and Azure that want Copilot adopted and governed.

Best for: Hardware, codec and vision startups that need a model or GPU pipeline made faster, ported or validated, with a benchmark they keep.

Best for: Industrial and pharmaceutical groups that want their own engineers taught to run AI projects before they buy a system.

Best for: Hardware startups that need firmware, apps and cloud built by one team, with model work brought in alongside.

Best for: Python-heavy teams that need senior engineers now, with AI built into how the work is delivered and reviewed.

Best for: Public bodies and research organizations that need messy data unified and throughput measured before any model work starts.

Best for: Product owners modernizing a platform who want AI inside the delivery process and in selected features, not a model built from scratch.

Best for: Founders and product owners who want an AI product validated and shaped before it is built, not just engineered to a spec.

Best for: Companies shipping a mobile or web product, including AI products that need everything around the model built properly.

Best for: Businesses hardening an AI prototype into a supportable production application, or embedding an LLM into software they already run.

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.

Best for: Product owners adding AI to an app that already has users, rather than starting from a model.

Best for: Spanish and Portuguese banks, insurers and public administrations wanting AI delivered by a large integrator with the data work around it.

Best for: Equipment manufacturers turning machine telemetry into a product feature their own service or R&D teams will keep running.

Best for: Diagnostics and pharma teams that need multi-omic and pathology data analyzed by named scientists, with a regulatory path in view.

Best for: Organizations whose AI plans depend on fixing the data layer first, especially in healthcare, public services and tourism.

Best for: Irish and UK organizations running on Microsoft platforms that want AI added to systems they already depend on.

Best for: Telecom operators and data-heavy product companies adding forecasting or anomaly detection to a platform they already run.

Best for: Consumer brands that need campaign volume at production economics a photoshoot cannot reach.

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.

Best for: Small firms and startups that want one embedded engineer to wire an LLM or agent into their existing tools on a modest budget.

Best for: Early-stage B2B product teams and smaller UK or Irish firms scoping a first voice agent, agent pipeline or Claude rollout.

Barcelona engineering partner that builds LLM, RAG and agent-based products for startups and scale-ups, and staffs CTO-vetted senior engineers into client teams. Offers AI chatbots and agents, AI automation, and CTO-as-a-Service alongside its delivery squads.

Wolf Logic is a West Midlands software company that rebuilt its delivery around an in-house AI orchestration platform, working on custom systems, legacy modernization and agent workflows for healthcare, industrial and public clients.

Healthcare-focused AI and software firm building clinical documentation, care-plan generation, claims automation and remote monitoring systems for providers and healthtech companies. Registered in Tallinn, with delivery offices in Kyiv and Warsaw and a US presence.

Neoteric is a Gdańsk software company founded in 2005, building generative AI and language-model applications alongside custom product development. Clutch named it a top artificial intelligence and generative AI company in 2023.

Best for: Founders who need a compliant retrieval-grounded product built and shipped in months, at a rate that leaves budget for the next iteration.

Best for: Founders shipping a consumer product that needs an AI feature designed, built and released inside one small team.

Apriorit is a software engineering firm with a Poznań office, founded in 2002, working in cybersecurity, systems programming and research-led development with an AI and machine-learning service line.

Best for: French mid-market firms adding a document-analysis or automation layer to a SaaS or internal platform they already operate.

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.

BID Company is a Milan data and AI consultancy building predictive models, language-model platforms and analytics architecture for Italian banks, insurers, pharmaceutical groups and transport operators.

Best for: Founders putting a model inside a consumer health, sports or wellbeing product.

Push Group is a London performance marketing agency with an in-house innovation lab building AI agents, running generative engine optimization and AI-assisted research alongside paid media and SEO.

Anadea is a software development firm headquartered in Alicante, founded in 2000, running an AI department it dates to 2019. Its AI work covers agentic systems, LLM applications, and automation for product companies.

Digica is a Manchester AI software company working in computer vision, sensor fusion and embedded machine learning, taking systems from prototype into production.

Unetiq is a Munich machine-learning agency and TUM spin-off building computer-vision, forecasting and language systems for industrial and B2B clients, with a second office in Amsterdam.

AlamedaDev is a Barcelona AI development studio building agentic AI, retrieval-augmented generation and document and audio intelligence systems.

Best for: Organizations wanting a private, self-hosted generative AI workspace over their own documents rather than a public LLM.

Best for: Banks and payment providers adding AI to platforms an established engineering partner already operates for them.

Best for: UK small businesses that want a working system and a named person answering the phone.

Best for: Companies that want an honest read on whether an AI project is worth building before commissioning one.

Best for: Founders and small UK firms building a first web or mobile product with an LLM feature inside it.

Best for: Consumer and healthcare brands needing campaign and compliance production at Nordic scale, with AI used in the making.

Almawave is a Rome natural-language and speech AI company building multilingual language models, conversational systems and clinical and administrative data interpretation for public administration, healthcare and finance.

BI4ALL is a Lisbon data and AI consultancy working on analytics platforms, machine learning and generative-AI automation for banking, insurance, pharmaceutical and energy clients.

Best for: Swedish B2B software and service companies that want search, paid media and AI-assistant visibility run by one marketing agency.

Best for: Dutch insurers, pension providers and care organizations building a Microsoft data platform and an in-house data team.

Nathean Analytics is a Dublin analytics consultancy building clinical and business intelligence platforms, data integration and reporting automation, and a founding industry member of Ireland's applied AI center.

Best for: Swiss institutions adding AI inside a larger systems program run by a long-established integrator.

AI Superior is a Darmstadt AI development company building computer vision, deep learning and language systems, from feasibility study through to deployment.

Innowise is a Warsaw software development company running full-cycle delivery across data, machine learning and generative AI alongside its wider engineering, cloud and staff-augmentation practice.

Best for: B2B and industrial firms that want to be named in AI answers and will fund a measured, ongoing program.

Best for: UK public bodies and publicly funded research programs building AI tools that keep expert reviewers in charge.

Best for: UK founders and small product teams who need a build partner at UK-regional rates, with AI as one component of a wider system.

Best for: Funded startups that need the interface and front end of an AI product designed and built while the model stays in-house.

Intellishore is a Copenhagen analytics and strategy consultancy pairing strategic advisory with data-science and AI delivery, weighted toward life sciences.

FELD M is a Munich data consultancy covering analytics, data engineering and privacy, with a data-science practice building predictive and classification models.

Best for: Italian enterprises and institutions that want AI scoped inside a wider process, governance or platform engagement.

Best for: Hungarian companies on Microsoft Dynamics 365 or Azure that want AI added inside the ERP, CRM and data systems they already run.

HLACIK is a Prague AI engineering boutique building edge computer vision, conversational agents and signal-analysis systems for public-safety, healthcare and enterprise clients.

Arana AI is a Munich-area generative-AI firm building language-model applications and assistants for healthcare and medical-technology clients, alongside its own accessibility assistant.

Brain Computing is a Rome software house and consultancy building business-process automation, custom CRM and learning platforms with AI agents and blockchain notarization for training bodies, retailers and healthcare clients.

DMBI Consultants is a Rome-area data-science consultancy building forecasting, text mining, satellite image analysis and predictive maintenance models for banks, utilities, telecom operators and public bodies.

Best for: Energy and utility firms that need the data platform built properly before any model work starts.

Best for: Italian distributors and wholesalers still matching orders, confirmations, delivery notes and invoices by hand.

Moxoff is a Milan mathematical-modeling and AI firm and Politecnico di Milano spin-off, building simulation, forecasting and generative-AI systems for industrial, healthcare and energy clients.

Elinext is a software development group headquartered in Warsaw, founded in 1997, with an AI and machine-learning service line alongside its platform practice. Its AI work covers retrieval-augmented systems, recommendations, and document processing.

Upscale Paris is a Paris AI consultancy working on operating-model change, from AI strategy and governance through prototype builds to adoption programs inside client teams.

Notch is a European AI-native product engineering company for mid-to-large enterprises. We build AI models, agents, and enterprise-grade custom software products. What do we do? 1. AI-native software development. We build new software products from scratch and modernize legacy applications. Senior engineers direct coding agents across the full lifecycle, from discovery to deployment and beyond. 2. Agentic systems. Autonomous agents built with architecture, testing discipline, and human oversight in place from the start. Entry points include an AI proof of concept and an AI minimum viable product. 3. Custom AI models. Purpose-trained models scoped to a specific business case. They outperform general-purpose models on accuracy, latency, data sovereignty, and running cost. 4. AI strategy consulting. The work before the build, turned into build-ready blueprints. Delivered as an AI Discovery Workshop or an AI Audit. 5. Agentic Experience Design. Designing how people work with agents across screen, chat, and voice. We make agent behavior transparent, controllable, and safe to delegate to. Who do we work with? Enterprise and mid-market companies with business-critical systems and a real engineering standard to meet. Typical clients have in-house technology teams and need depth those teams don't have on staff. Problems Notch is hired to solve "We know AI belongs in this process. We do not know what changes around it." An AI Discovery Workshop or AI Audit maps the process, the data behind it, and the operating model that has to change with it. Output is a build-ready blueprint. "An internal team built a working AI prototype. Now it has to run in production." A code and architecture review, a security and data isolation assessment, an evaluation baseline, and a decision on what to keep and what to rebuild. Then the production build, with the same team staying on. "Our core system is old, and every change takes a quarter." Agents map the codebase in days, not mon

Datalyo is a Lyon data and AI consultancy building data platforms, machine-learning models and business intelligence for industrial, retail and public-sector clients.

Scaling CIRFOODs tender process from 4 -> 45 per year with the same team.

AdamI is an Amsterdam AI consultancy and implementation firm building assistants, chatbots and analysis tools for organizations that keep their engagements confidential.

AISO Hub is a Lisbon AI-search optimization agency working on structured data, answer-shaped page architecture and citation monitoring so brands are quotable by ChatGPT, Perplexity, Gemini and AI Overviews.

Blackbirds is a Rotterdam AI consultancy pairing strategy with engineering for planning, document, forecasting and compliance work, mainly for logistics, public sector and industrial clients.

DataGenius is a Lyon machine-learning consultancy building predictive models, language processing and production data-science modules for pharma, health and SME clients.

Konektor Group is a Barcelona AI automation agency building AI agents, chatbots and process automation for B2B and healthcare clients.

Stratify AI is a Budapest AI consulting and implementation firm building contract summarization, natural-language database query and recruitment screening systems for business operations.

AI Manager Agency is a French technology service provider that helps startups and small businesses implement practical AI automation tools instead of hiring expensive, full-time AI engineers.