AI for the healthcare sector

AI for healthcare in Switzerland

Clinics, practices, healthcare providers: we automate admin and document management with AI, while keeping sensitive data under control. Open source, European hosting.

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🇪🇺 Europe
Falkenstein
Helsinki
Nürnberg

Hetzner · Europe

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The Swiss healthcare sector faces two tensions that are difficult to reconcile: growing pressure on administrative productivity, and some of the world's strictest data protection requirements. The revised LPD, medical professional secrecy, FHIR/CH interoperability standards, and LAMal constraints create a framework that most general-purpose AI tools do not meet.

Kleap enables medical practices, clinics, care networks, and hospitals to deploy custom business AI tools: documentation assistants, patient portals, clinical dashboards, triage tools, and administrative process automation. The infrastructure relies on European servers (Hetzner, EU), the models used are open source and run in the EU. Your data is never reused to train third-party models.

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AI that's genuinely useful for healthcare

More time for patients, less paperwork.

Lighter admin

Appointment booking, reminders, letters, data entry: we automate the tasks that weigh on your teams.

Document management

Filing, extraction and summarization of documents, with human validation.

Protected sensitive data

Open source models on European infrastructure, with nothing sent to third-party APIs.

Integration with the practice

We adapt to your tools and your organization, without turning everything upside down.

The most common AI use cases in Swiss healthcare

AI is already operational in many Swiss institutions. The best-documented gains concern tasks with high repetitive cognitive load: writing reports, transcribing consultations, managing records. Here are the most frequently deployed use cases, by institution type.

  • Solo or group practice: automatic consultation transcription, generation of referral letters and reports, incoming email triage, patient reminders
  • Clinic or outpatient centre: patient record summaries, automation of team reports, secure patient portal with personalized FAQ
  • Care network or hospital group: operational dashboard, AI decision-support agent for administration, inter-service process automation
  • Medico-social facility (EMS): resident follow-up documentation, family communication, assisted care planning
  • Specialist practice (radiology, oncology, psychiatry): assisted image annotation, follow-up data structuring, protocol drafting support

Data sovereignty: what the LPD and medical secrecy actually require

In Switzerland, health data is sensitive data under the LPD (Federal Act on Data Protection, in force since September 2023). Its processing involves reinforced obligations: explicit legal basis, patient information, appropriate technical security, and purpose limitation.

General-purpose consumer AI tools (ChatGPT, Gemini, standard Copilot) are not designed for this context: their terms of use generally permit data reuse for training purposes, which is incompatible with medical secrecy and the LPD as applied to identifying data.

Kleap relies on infrastructure hosted in Europe (Hetzner servers, EU), open source models running in that controlled environment, and data processing contracts that exclude any reuse. This is not a marketing promise: it is the direct consequence of the infrastructure choice.

  • Exclusively European hosting (Hetzner, Falkenstein / Helsinki / Nürnberg)
  • Open source models deployed in the EU, no transfer to American data centers
  • Data not reused for training third-party models
  • Architecture compatible with the revised LPD and medical secrecy requirements
  • Traceability of AI operations (who requested what, when, on which data)

Checklist: how to evaluate an AI solution for your healthcare institution

Given the proliferation of AI offerings in healthcare, choosing the right solution is not straightforward. Here are the criteria that Swiss IT managers and medical directors should verify before any deployment.

  • Data residence: is data processed and stored exclusively in the EU or Switzerland?
  • Reuse policy: is data used to improve the provider's models?
  • EHR/HIS integration: does the solution interface with your practice software (Medidata, Praxissoftware, etc.) or your HIS?
  • Traceability and auditability: is the tool a black box, or can the decisions made be verified?
  • LPD compliance: does the data processing contract cover the obligations of the data controller?
  • FHIR/CH compatibility: can the solution align with Swiss interoperability standards?
  • Training and support: does the deployment include team training and a designated technical contact?

Administrative automation: where AI frees up clinical time

Clinical documentation accounts for a growing share of healthcare professionals' time in Switzerland. Physicians devote a significant portion of their working time to administrative tasks. AI can reduce this burden without replacing clinical judgment.

The gains measured in Swiss institutions that have deployed AI solutions cover mainly the following tasks.

  • Medical consultation transcription: automatic audio-to-text conversion, structured into history, symptoms, medication, treatment plan
  • Generation of referral letters and discharge reports from clinical notes
  • Automatic summary of large patient files before a consultation
  • Drafting of team meeting minutes and internal reports
  • Triage of incoming emails and messages, prioritization of urgent cases
  • Generation of patient content (post-operative instructions, FAQ, reminders)

Patient portals and back-office tools: beyond transcription

Most discussions about AI in healthcare focus on clinical documentation. But the needs of Swiss healthcare institutions go much further: patient information portals, internal resource management tools, operational dashboards, front-line AI agents for administrative requests.

Kleap allows these tools to be built on a custom basis, without code, based on your institution's real needs. Each tool is hosted on your own deployment infrastructure, with your own data governance rules.

  • Patient portal: dynamic FAQ, assisted appointment booking, personalized instructions, automatic reminders
  • Administrative AI agent: responses to common requests (schedules, access, billing, insurance), escalation to a human when necessary
  • Operational dashboard: visualization of patient flows, tracking of key indicators, automatic alerts
  • Internal HR tool: schedule management, onboarding of new staff, internal knowledge base
  • Reporting module: automatic generation of reports for management, insurers, or health authorities

Risks, limitations, and governance: what you need to know before deploying

AI in healthcare carries real risks that every medical or IT manager must have assessed before deployment. Ignoring these risks exposes the institution not only to technical failures but also to legal liability issues and patient trust problems.

The main points of vigilance in the Swiss context.

  • Hallucinations: language models can generate plausible but false information. Any clinical content produced by AI must be reviewed and validated by a qualified professional before use
  • Medical liability: under Swiss law, clinical responsibility remains with the physician or institution, regardless of the AI assistance used
  • Algorithmic bias: models trained on non-representative data may produce recommendations that are unsuitable for certain populations
  • Vendor dependency: an AI solution that stops working or changes its terms can paralyze critical processes
  • Insufficient training: adoption without adequate team training leads to incorrect use and increased error risk
  • Access governance: define who can use which AI tools, on which data, with what level of supervision

Three paths to deploying AI in your healthcare institution

Kleap offers three engagement options adapted to the size and digital maturity of your organization. There is no one-size-fits-all solution: the right approach depends on your internal resources, timelines, and objectives.

  • Build by partner agency (Lionscreative): a business AI tool built for you, from specification to production, with data governance support
  • Introduction to a specialized healthcare AI provider: if your needs go beyond our scope, we connect you with the right partners in the Swiss ecosystem
  • Kleap Enterprise self-serve: for teams that want to build and deploy their own business AI tools themselves, with our sovereign infrastructure and support

Swiss context: where does AI adoption stand in healthcare?

Switzerland presents a characteristic paradox: healthcare institutions that are among the best technically equipped in the world, but AI adoption that remains uneven and often unstructured. Several structural factors explain this situation.

  • Absence of a formalized national AI-in-health strategy (unlike some other European countries)
  • Fragmentation of the system (multiple insurers, autonomous cantons, private and public institutions)
  • Many Swiss professionals already use AI at work, often without a defined institutional framework
  • CHUV is testing the Meditron medical model from May 2026 onwards: a strong signal of institutionalization
  • The NAIPO initiative (AI-assisted precision oncology) demonstrates the viability of a sovereign AI infrastructure for healthcare
  • HIN and AlpineAI have already deployed Swiss HealthAssist to several hundred practitioners in French-speaking Switzerland

What Kleap is not: an honest clarification of positioning

Kleap is not a certified medical device (MD) software in the sense of ODim or the European MDR regulation. Kleap does not replace a clinical information system (CIS/HIS) or medical practice software.

Kleap is a business AI tool building platform. It allows healthcare institutions to create interfaces, automations, and AI agents that connect to your existing systems or work alongside them, without requiring regulatory certification for direct non-clinical uses (administrative, documentation, patient information, back-office).

For uses involving direct clinical risk (diagnostic support, prescribing, urgent triage), Kleap recommends working with certified specialized solutions and integrating AI outputs into an explicit human validation process.

  • Covered uses: documentation, reporting, patient portals, administrative tools, dashboards, front-line agents
  • Uses not covered without specialized support: clinical diagnostic support, automated drug prescribing, autonomous urgent triage
  • Always with human validation: AI outputs are drafts or suggestions, never autonomous final decisions

How to deploy an AI tool in your institution: key steps

01

Define the scope and priority use cases

Identify the 2 to 3 tasks that take up the most administrative time in your institution. Clinical documentation, patient communication management, and internal reports are generally the most effective starting points.

02

Map data flows and regulatory constraints

Before any deployment, identify what data the AI tool will process (personally identifying data, medical data, financial data). Check LPD, LAMal constraints and, where applicable, the requirements of your insurer or cantonal supervisory authority.

03

Choose the infrastructure and validate compliance

Opt for an infrastructure with guaranteed data residence in the EU or Switzerland. Verify the existence of an LPD-compliant data processing contract. If the tool interfaces with your CIS/HIS, assess the integration risks with your IT manager.

04

Train teams and define governance rules

A successful deployment depends as much on training as on the tool itself. Define who can use the tool, on which data, with what level of human validation required. Communicate clearly to teams that AI outputs are suggestions, not final decisions.

05

Deploy gradually and measure results

Start with a pilot service or a specific type of task. Measure the actual time saving, user satisfaction, and the absence of incidents related to AI output quality. Adjust before expanding the deployment to other teams or departments.

Sovereign AI vs. general-purpose tools: what actually changes for a Swiss institution

Many Swiss healthcare professionals already use tools like ChatGPT or Copilot. This table summarizes the concrete differences for use in a Swiss medical context.

CriterionKleap (sovereign EU infrastructure)General-purpose tools (ChatGPT, standard Copilot)
Data residenceHetzner EU servers (Germany, Finland)USA or unspecified region depending on the agreement
Data reuse for trainingExcluded by contractPermitted under standard terms of use
LPD compliance / medical secrecyArchitecture designed for complianceRequires specific configuration that is not guaranteed
Integration with business processesCustom tools per specialty or institutionGeneral-purpose use, manual adaptation required
Traceability and governanceUsage logging, configurable access rulesLimited in standard offerings
Deployment supportPartner agency + dedicated supportOnline documentation, community support

Sovereignty

Health data does not leave

Health data is among the most sensitive there is. We treat it accordingly.

European hosting

Infrastructure in Europe (Hetzner), no US cloud.

No reuse

Your data is not used to train third-party models.

Traceability

Every automated operation is logged.

swissIa.iaSanteSuisse.localContextTitle

French-speaking Switzerland: Genève (HUG, private clinics), Vaud (CHUV, Arcas care network, Lausanne practices), Fribourg (HFR), Valais (HVS / RSV), Neuchatel (RHNe). These institutions face the same LPD constraints and the same administrative productivity challenges.
The canton of Vaud is piloting Meditron at CHUV from May 2026: a signal of institutionalization of medical AI in French-speaking Switzerland.
The FMH (Swiss Medical Association) has published a practical guide on AI in medicine (6.7 of the practical guide on legal bases): a reference framework for Swiss physicians.
HIN (Health Info Net) is the secure communication infrastructure for Swiss healthcare professionals. Their deployment of Swiss HealthAssist validates market interest in sovereign AI solutions.
AI in healthcare in Genève is developing primarily in medical applications according to Heidi.news (2026): early diagnosis, oncology, precision medicine. A favorable context for complementary back-office tools.

Frequently asked questions

Is using AI with patient data legal in Switzerland?

Yes, provided the revised LPD (in force since September 2023) is respected and, for medical data, professional secrecy (art. 321 CPS). This requires an explicit legal basis for processing, compliant data residence, and no reuse of data for undeclared purposes. AI tools hosted on European infrastructure with an LPD-compliant processing contract meet these requirements for administrative and documentary uses.

What is the difference between Kleap and a certified medical device software?

Certified medical software (MD under ODim or the MDR regulation) is designed for direct clinical acts (diagnostic support, prescribing, vital parameter monitoring). Kleap is a business AI tools platform covering administrative, documentary, and organizational uses. These two categories are complementary, not competing.

Is my patients' data stored in Switzerland?

Kleap infrastructure is hosted on Hetzner servers located in Europe (Germany and Finland). Data does not transit through American servers. We do not claim hosting 'in Switzerland' in the strict sense, but the infrastructure is entirely within the European legal space, compatible with LPD requirements for Swiss institutions.

Can AI integrate with my practice software or HIS?

This depends on the interfaces available in your software. Tools built with Kleap can interface via open APIs or standard data exports (including FHIR/CH if your HIS supports it). For complex integrations with proprietary software (Medidata, etc.), the Lionscreative partner agency can assess technical feasibility.

What happens if the AI makes an error on medical content?

All content produced by AI in Kleap is a draft or suggestion. Clinical responsibility remains entirely with the healthcare professional who validates and signs the final document. No AI system should be used as an autonomous decision-maker in a medical context, and Kleap is designed to operate within an explicit human validation workflow.

Is Kleap suitable for a solo practice or only for large institutions?

Both. A general practitioner in a solo practice can benefit from automated documentation and patient communication tools. A care network or hospital can deploy more complex tools (dashboards, multi-service AI agents). The approach is modular and adapts to the size of the organization.

Which AI models does Kleap use?

Kleap relies on open source models deployed on European infrastructure. For healthcare applications, we prioritize models for which data residence and processing control can be guaranteed contractually. We do not use general-purpose consumer models whose terms permit data reuse.

How does Kleap handle training of clinical teams in AI?

The Lionscreative partner agency offers deployment support that includes user training. This covers tool usage, best practices for prompting in a medical context, defining access governance rules, and establishing an internal AI coordinator.

Can AI help with billing and insurer management (Tarmed, TARDOC)?

AI tools can automate certain parts of the documentation process that feeds into billing (structuring of procedures, drafting of supporting documents). Validation and submission to insurers remains the responsibility of the certified billing software and the responsible healthcare professional. Kleap is not a medical billing software.

What is the typical deployment timeline for an institution?

For a simple tool (documentation assistant or informational patient portal), deployment can be operational in 2 to 6 weeks. For more complex tools integrated with existing systems (CIS, HIS, multi-service workflow), the timeline ranges from 2 to 4 months depending on the complexity of integrations and internal validation processes.

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AI for Healthcare in Switzerland | Clinics, Practices, Providers