From idea to deployment

AI Strategy for Swiss companies

We help you frame your AI strategy: identify the right use cases, prioritize what creates value, and move to delivery. No hype, real results.

Talk to an expertDescribe my need
Opportunity auditRoadmapQuantified use cases

14'036+ sites created in the last 30 days

actif
🇪🇺 Europe
Falkenstein
Helsinki
Nürnberg

Hetzner · Europe

US cloud
Opportunity audit
Roadmap
Quantified use cases

A growing share of Swiss businesses already uses some form of artificial intelligence, but few have integrated it at the core of their strategy. The gap is not technological: it is organisational. The recurring obstacles are a lack of internal skills, uncertainty about real costs, and the absence of a clear data governance framework. Kleap helps Swiss businesses overcome these barriers, from the initial audit through to the deployment of the first production tools, with 100% European hosting and end-to-end nLPD compliance.

14'036+
sites created in the last 30 days
16
languages
100%
European hosting
0
US cloud

Our approach

An AI strategy is first about clear decisions.

Opportunity audit

We map your processes and pinpoint where AI creates the most value, fast.

Roadmap

A roadmap prioritized by impact and feasibility, not a list of gadgets.

Quantified use cases

For each lead, the effort, expected gain and risks, so you can decide with confidence.

From framing to build

We do not stop at the slide deck: we build and deploy what we recommend.

Why Switzerland is at a crossroads on AI

The Swiss ecosystem has real strengths: ETH Zurich and EPFL rank among the world's leading AI institutions, private investment is accelerating, and companies like ABB, UBS, and Kuehne+Nagel have already undergone significant transformations. Yet many Swiss businesses have not yet started a structured approach. For SMEs in particular, the adoption rate remains well below that of large enterprises. This lag is not inevitable: it represents a window of competitive advantage for those who act now.

  • A significant share of Swiss businesses uses AI in some form
  • A minority have integrated it as a central strategic lever
  • The internal skills deficit is the number-one barrier, ahead of cost and regulation
  • The most advanced sectors: finance and banking, industry and robotics, healthcare, insurance

The three Kleap offerings for your AI strategy

Kleap offers three engagement models depending on your situation and internal resources. Some companies want to be supported end-to-end by a team that builds for them. Others already have internal resources and are looking for the right specialised provider. Others still want direct access to the platform and want to move forward independently. These three paths are not mutually exclusive: they can be combined depending on the project phase.

  • Custom build: the Lionscreative team designs and delivers your internal AI tools (client portals, dashboards, AI agents, process automation)
  • Matchmaking: Kleap connects you with the right provider in its network based on your sector, size, and constraints
  • Kleap Enterprise self-serve: access the AI platform to build and deploy your tools without a developer, with onboarding support

What AI can do for your business: concrete use cases

Before choosing a tool or a provider, the most useful step is to identify where AI genuinely creates value in your organisation. The most common use cases among Swiss SMEs span several business domains: automating repetitive low-value tasks, analysing data to support decisions, customer service, and content generation. Here are the most widely deployed categories.

  • Administrative process automation: document processing, data extraction, automatic reporting
  • Data analysis and decision support: intelligent dashboards, predictive alerts, consolidation of heterogeneous sources
  • Customer service and support: conversational agents available 24/7, intelligent escalation to humans
  • HR management and recruitment: application sorting, skills analysis, automated follow-up
  • Marketing and personalisation: granular segmentation, segment-tailored content, behaviour analysis
  • Cybersecurity: anomaly detection, access monitoring, real-time alerts
  • Back-office and logistics: inventory optimisation, workload forecasting, supplier coordination

Common barriers and how to overcome them

Companies that are not moving forward on AI rarely lack the will. The obstacles are concrete and recurring. Understanding them helps avoid the most costly mistakes and structure a realistic approach from the start.

  • Lack of internal skills: the solution is not to hire a data scientist before having a validated use case. Start with upskilling existing teams and no-code/low-code tools suited to your processes.
  • Perceived cost too high: a well-scoped first AI project can start with a modest budget if the scope is precise. The initial audit clarifies the cost-to-value ratio before any commitment.
  • Data governance: many Swiss companies have not inventoried their data. Kleap works with EU-hosted data, without reuse for model training.
  • Cultural and organisational resistance: AI does not replace teams, it removes low-value tasks from them. Training and internal communication are levers just as important as technology.
  • nLPD and GDPR compliance: every implementation is designed from the start to comply with the revised Swiss Data Protection Act and the European GDPR.

Our method: four steps from scoping to deployment

An AI strategy is only valuable if it leads to tools that work in production. Our method is designed to avoid projects that stall at the report stage and to produce measurable results at every phase.

  • Step 1 - Opportunity audit (2 to 4 weeks): interviews with key teams, review of existing processes and tools, identification of high-potential use cases, prioritisation by impact and feasibility
  • Step 2 - Costed roadmap (1 to 2 weeks): AI scenarios per use case, resource and timeline estimates, data governance plan, risk identification
  • Step 3 - Structured pilot projects (1 to 3 months): development of first tools within a limited scope, measurement of indicators defined upfront, adjustments before scaling
  • Step 4 - Deployment and support: production deployment on EU infrastructure, user training, indicator monitoring, evolution based on field feedback

Data governance and compliance: what is non-negotiable

Trust in AI starts with control over data. In Switzerland, the nLPD (revised Federal Act on Data Protection, in force since September 2023) and the European GDPR impose concrete obligations on the collection, processing, and hosting of data. For companies working with European clients or handling sensitive data, these requirements are not optional.

  • 100% European hosting: all data processed by Kleap tools is hosted on Hetzner servers located in the European Union
  • Open-source models: Kleap relies on open-source AI models running on EU infrastructure, with no data transfer to American clouds
  • Data not reused: your data is not used to train third-party models
  • Privacy-by-design nLPD compliance: architectures are designed from the start with Swiss regulatory constraints in mind
  • Traceability and logs: data flows are documented to meet internal or external audit requirements

Which sectors and company sizes

Kleap primarily works with SMEs and mid-size companies in French-speaking and German-speaking Switzerland, as well as digital departments of larger organisations. The platform is suited to companies that have processes to automate, data to unlock value from, or internal tools to build, without necessarily having a dedicated technical team.

  • Finance and fiduciaries: data entry automation, reconciliation, client reports
  • Commerce and distribution: personalisation, inventory management, customer service
  • Real estate and construction: document analysis, site monitoring, lead qualification
  • Healthcare and paramedical: triage, scheduling, administrative management
  • Training and HR: automated onboarding, skills analysis, matching
  • Industry and logistics: predictive maintenance, flow optimisation, traceability
  • Professional services and legal: document research, assisted drafting, compliance

What this offering is not

Clarifying what Kleap does not offer is as useful as describing what we do. Several types of projects do not fit our positioning, and it is better to say so clearly.

  • Not a traditional strategy consultancy: we do not deliver a report without implementation
  • Not a generalist software vendor: we build custom tools suited to your processes, not standardised licences
  • Not a host for sensitive data outside the EU: all infrastructure is European
  • Not a replacement for your teams: AI enhances existing skills, it does not substitute for human decisions
  • Not suited to projects without an identified use case: if you are simply looking to 'do AI' without a specific business problem, the initial audit is the step that clarifies scope before any commitment

Why digital sovereignty matters for Swiss businesses

Technological sovereignty has become a recognised strategic issue, including by Swiss institutions. Using AI tools whose data goes to American clouds creates regulatory dependencies, compliance risks, and governance questions that many companies have not yet measured. Kleap is built on a European stack: Hetzner for hosting, open-source models running in the EU, with no dependency on American vendors for data processing.

  • No dependency on non-EU clouds for data processing
  • Open-source models hosted and executed on EU infrastructure
  • Compliant with the requirements of companies working with Swiss or European public bodies
  • Resilience: no risk of disruption linked to changing American terms of service
  • Transparency: you know where your data is hosted and how it is processed

How an engagement works

01

Initial contact and scoping (Day 0 to Day 5)

A first 45 to 60-minute conversation to understand your context, key processes, constraints, and objectives. No technical prerequisites. We leave with an audit proposal tailored to your size and sector.

02

Opportunity audit (2 to 4 weeks)

Interviews with business teams, review of tools and data flows, identification and prioritisation of use cases. Deliverable: an opportunity map with an assessment of potential and feasibility for each case.

03

Roadmap and validation (1 to 2 weeks)

Translating opportunities into concrete scenarios with timelines, resources, and success indicators. Validation with management before any development. At this stage, you have a clear picture of what you are going to build and why.

04

Build and deployment (4 to 12 weeks depending on scope)

Tool development on EU infrastructure, testing with user teams, adjustments, production deployment. User training and documentation. Performance indicator monitoring in the 30 days post-deployment.

Kleap vs the alternatives: what actually changes

Swiss businesses looking to move forward on AI have three main options. Here is how they compare on the criteria that matter for an SME or mid-size company.

CriterionKleapTraditional consultancyFreelance consultant
Final deliverableTools deployed in productionStrategic report and roadmapVaries by profile
Data hosting100% EU (Hetzner)Depends on partnersDepends on tools used
nLPD complianceBuilt in by designAdvised, not implementedTo be checked case by case
Access without a technical teamYes, no-code/low-code platformNoPartial
Time to first result4 to 8 weeks3 to 6 months (report)Variable
Engagement modelAudit + build + self-serveFixed-price or time-and-materialsTime-and-materials or fixed-price
Referral if not the right fitYes, partner networkNoNo

swissIa.strategieIaSuisse.localContextTitle

French-speaking Switzerland (Genève, Lausanne, Fribourg, Neuchâtel, Sion): high concentration of SMEs in services, finance, education, and healthcare, with heightened sensitivity to data protection and digital sovereignty
Swiss academic research: several university initiatives and universities of applied sciences make AI tools and expertise available to SMEs in western Switzerland. Kleap complements these offerings on the implementation and deployment side.
Swiss nLPD (in force September 2023): Switzerland has its own data protection legal framework, which applies independently of the GDPR and imposes specific requirements on companies processing data of Swiss residents
Scarcity of AI profiles in Switzerland: the AI job market remains very tight, making no-code approaches and platforms accessible without a technical team particularly relevant for SMEs
Hetzner EU as reference infrastructure: compliant with the requirements of Swiss and European public procurement, which mandates non-US cloud hosting for sensitive data

Frequently asked questions

Where do we start when we have never done an AI project?

The best starting point is a specific business problem, not a technology. Begin by identifying a repetitive task that consumes high-value time, or a decision-making process that would benefit from being data-driven. Kleap's initial audit is designed to start from scratch and help you prioritise, with no technical prerequisites on your side.

What budget should we plan for an AI strategy as an SME?

Budgets vary with scope. An initial audit and roadmap represent a modest investment compared to a full development project. A first tool deployed in production for a Swiss SME can be built in 4 to 8 weeks. Contact us for an estimate based on your specific situation: the first scoping conversation is without commitment.

Will our data be processed outside Switzerland?

Kleap's infrastructure is hosted on Hetzner servers located in Germany, within the European Union. Data is not transferred to American clouds and is not reused to train third-party models. Compliance with the Swiss nLPD and the GDPR is built into the architecture.

Do we need a technical team or a data scientist already?

No. Kleap is designed for companies without an internal AI team. The platform allows tools to be built without a developer for common use cases. For more complex projects, the Lionscreative team handles the full development.

What is the difference between an 'AI strategy' and 'AI implementation'?

An AI strategy answers 'where and why?': which processes to target, what value to create, in what order. Implementation answers 'how?': which tools to build, with what architecture, and what governance. Kleap covers both: we do not deliver a strategic report without the ability to build what comes next.

How do we avoid AI projects that stall at the PowerPoint stage?

The main risk is commissioning an audit or strategy from a firm that lacks the capacity to build afterwards. At Kleap, the same team that scopes your strategy is the one that implements it. Milestones are defined with concrete deliverables at each stage, not just a final document.

How long does a first AI project take from end to end?

From the initial audit to the first tool deployed in production, allow 8 to 16 weeks for a well-defined scope. An audit alone takes 2 to 4 weeks. The roadmap takes an additional 1 to 2 weeks. Development and deployment take 4 to 12 weeks depending on complexity.

Is nLPD compliance really a barrier, or can we proceed anyway?

The nLPD is not a barrier if it is built in from the start: tool selection, data localisation, access rights, documentation of processing activities. Problems arise when you deploy first and try to comply afterwards. Kleap's approach treats regulatory constraints as a design parameter, not an end-of-project audit.

Can Kleap build internal tools (back-office, client portals, dashboards)?

Yes. Internal tools represent the majority of enterprise projects: client portals, operational dashboards, AI agents for specific business processes, back-office tools. These are applications deployed on your infrastructure or on Kleap's infrastructure, not public-facing consumer websites.

Does Kleap work with companies outside French-speaking Switzerland?

Yes. Kleap works with businesses across Switzerland (French-speaking, German-speaking, and Ticino) as well as European companies looking for a partner with sovereign EU infrastructure. The platform is available in 16 languages. For projects with a strong local or in-person dimension, a referral to the appropriate regional partner is possible.

Related topics

Business AI audit in SwitzerlandAI Training for Companies in SwitzerlandAI for SMEs in Switzerland

Where can AI win for you?

Let us talk about your business. Together we spot the first high-impact use cases.

Request a Custom Demo

Tell us about your team and we'll reach out within 24 hours.

We'll never share your information. Expect a response within 24h.

AI Strategy for Swiss companies | Frame and deploy AI