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CLEEV
Zurich · Switzerland

Build smarter. Automate faster. Scale with AI.

CLEEV is an AI and software engineering company in Zurich. We help organisations transform their operations through AI automation, intelligent agents, custom AI solutions and modern software.

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How CLEEV works: information flows from your business, through data and AI, into automation and finally action.

01Position

AI should do more than generate answers. It should transform how your business works.

CLEEV combines artificial intelligence, automation, software engineering and data to create intelligent business systems built around real operational needs.

How we work
01Artificial intelligence
Models that understand language, documents and data.
02Automation
Workflows that act on what the models understand.
03Software engineering
Applications and platforms built to last.
04Data
The governed foundation everything depends on.

02Core services

Six capabilities. One engineering practice.

From the first automated workflow to an AI-native platform, every engagement draws on the same disciplines — so what we build fits together.

  1. 01

    AI Automation

    Transform repetitive business processes into intelligent automated workflows.

    • Business process automation
    • Intelligent workflows
    • n8n automation
    • Document automation
    • CRM / ERP workflows
    • Operational automation
    Fig. 02.1 — AI Automation
    Explore AI Automation
  2. 02

    AI Integration

    Integrate advanced AI capabilities into existing applications, platforms and business systems.

    • OpenAI
    • Claude
    • Gemini
    • Open-source LLMs
    • API integration
    • ERP / CRM integration
    Fig. 02.2 — AI Integration
    Explore AI Integration
  3. 03

    AI Agents

    Build intelligent assistants capable of helping customers, employees and business operations.

    • Customer agents
    • Internal assistants
    • Voice AI
    • Sales assistants
    • Research agents
    • Multi-agent workflows
    Fig. 02.3 — AI Agents
    Explore AI Agents
  4. 04

    Custom AI Solutions

    Develop tailored artificial intelligence platforms around specific business requirements.

    • AI SaaS
    • Enterprise AI applications
    • RAG systems
    • Document intelligence
    • Semantic search
    • Recommendation systems
    Fig. 02.4 — Custom AI Solutions
    Explore Custom AI Solutions
  5. 05

    Software Engineering

    Build scalable applications and digital platforms engineered for long-term business use.

    • Web applications
    • SaaS platforms
    • Backend development
    • APIs
    • Enterprise systems
    • Cloud applications
    Fig. 02.5 — Software Engineering
    Explore Software Engineering
  6. 06

    AI Strategy & Transformation

    Identify high-value AI opportunities and create a practical path from concept to deployment.

    • AI readiness
    • Use-case discovery
    • AI roadmap
    • Architecture
    • Proofs of concept
    • Transformation strategy
    Fig. 02.6 — AI Strategy & Transformation
    Explore AI Strategy & Transformation

03How CLEEV works

From complexity to intelligence.

  1. 01

    Discover

    We map processes, data and pain points with the people who run them.

  2. 02

    Design

    We define the target workflow, architecture and how success will be measured.

  3. 03

    Build

    We engineer the solution in short iterations, tested on your real data.

  4. 04

    Integrate

    We connect it to the systems, permissions and people it depends on.

  5. 05

    Deploy

    We release to production with monitoring, logging and clear ownership.

  6. 06

    Scale

    We measure, improve and extend what works to further processes.

04AI automation in motion

From inbox to system of record.

Unstructured inputs arrive. The AI layer understands them, automation validates and routes, and your business systems are updated — with people approving the exceptions.

Simulated workflow: inputs flow through the AI layer and the automation layer into business systems.01 INCOMINGINPUT 01EmailINPUT 02PDF invoiceINPUT 03CRM leadINPUT 04Customer request02 AI LAYERAI · 01UnderstandAI · 02ClassifyAI · 03ExtractAI · 04Reason03 AUTOMATIONSTEP · 01ValidateSTEP · 02RouteSTEP · 03UpdateSTEP · 04Generate04 BUSINESS SYSTEMSSYSTEM 01CRMSYSTEM 02ERPSYSTEM 03DatabaseSYSTEM 04EmailSYSTEM 05Dashboard

Simulation · illustrative data

01

Understands unstructured input

Emails, scans and free-text requests are read for meaning, not matched against brittle templates.

02

Validates before it acts

Every extracted value is checked against rules and source systems before anything is written.

03

Keeps people in control

Exceptions and high-impact actions are routed to the right person with the context already prepared.

05AI agents

Agents that finish the task.

A useful agent does more than answer. It reads, retrieves, decides what to do next and acts in your systems — within the permissions you define.

  • Grounded in your knowledge

    Answers and actions draw on approved sources, not the open internet.

  • Acts through approved tools

    Agents call only the systems and operations they are permitted to use.

  • Every step is traceable

    Each retrieval, decision and action is logged and reviewable.

Ask CLEEV AI

Concept demo
User: Summarise this customer request and update the CRM.
  1. Pending

    Reading request

    Email from Example AG · 2 attachments

  2. Pending

    Searching knowledge

    Delivery terms · account history

  3. Pending

    Identifying customer

    Example AG · key account

  4. Pending

    Preparing summary

    Intent: change delivery date and quantity

  5. Pending

    Updating CRM

    Case updated · owner notified

Working…

Conceptual demonstration — not connected to live systems.

06Enterprise knowledge

Turn your business knowledge into intelligence.

Your organisation already knows the answers. We connect documents, databases and systems into a knowledge layer that your teams — and your AI — can ask in plain language.

Company documents

Contracts · reports · manuals

Databases

ERP · CRM · SQL

Policies

Handbooks · procedures

Internal systems

Wiki · tickets · drives

CLEEV knowledge layer

  • Parse & chunk01
  • Embed & index02
  • Link entities03
  • Apply permissions04

AI assistant

Illustrative example

What notice period applies to our supplier contracts?

Supplier contracts use a 90-day notice period, unless a different term was agreed in the individual contract[1][2].

  • [1] Procurement policy · §3.2
  • [2] Supplier framework agreement · §11

Source-backed · permissions respected

Retrieval-augmented generation
Answers are generated from your own documents, not from what a model happens to remember.
Semantic search
People find information by meaning — the way they would ask a colleague — not by guessing keywords.
Enterprise knowledge
Scattered files, systems and know-how become one searchable, current body of knowledge.
Source citations
Every answer shows where it came from, so people can verify before they act.
Access-controlled AI
Users only receive answers built from content they are already allowed to see.
Vector databases
Content is stored by meaning, so related passages are found instantly at scale.
Knowledge graphs
Relationships between customers, products, contracts and people are made explicit and queryable.
RAG & Knowledge Systems

07Engineering

AI is only as strong as the engineering behind it.

Models change every few months. The software around them has to last for years. We engineer the whole system — not only the part that makes the demo work.

  • 01Custom Software
  • 02SaaS Development
  • 03APIs
  • 04Cloud Architecture
  • 05Data Engineering
  • 06System Integration

Reference architecture

  1. Experience layer

    Web apps · portals · chat · voice

  2. Application layer

    Business logic · workflows · APIs

  3. AI layer

    Models · agents · retrieval · evaluation

  4. Integration layer

    CRM · ERP · webhooks · events

  5. Data layer

    PostgreSQL · vector stores · warehouses

  6. Infrastructure layer

    Cloud · containers · CI/CD · monitoring

08Technology

Technologies we build with.

We choose tools for the problem, not the other way round — and design systems so that models and providers can be replaced as the field moves.

AI
  • OpenAI
  • Anthropic
  • Gemini
  • Hugging Face
  • Open-source LLMs
Engineering
  • Python
  • TypeScript
  • React
  • Next.js
  • Node.js
Automation
  • n8n
  • APIs
  • Webhooks
  • Event queues
Data
  • PostgreSQL
  • Vector databases
  • Knowledge graphs
Infrastructure
  • Docker
  • Cloud
  • CI/CD
  • Observability

Product names are trademarks of their respective owners. Listing indicates technologies we work with, not partnerships or endorsements.

09Industries

Built around how your industry actually works.

01 / 10

Financial Services

Operational challenge
High volumes of documents, strict confidentiality and regulatory scrutiny make manual processes slow and AI adoption cautious.
CLEEV capability
Access-controlled document intelligence and auditable automation.
Example scenario
An onboarding assistant that extracts data from client documents, flags missing items and prepares files for compliance review — with every step logged.
Applications in Financial Services

10Switzerland

Zurich
47.3769° N, 8.5417° E

Engineered in Switzerland. Built for global business.

CLEEV is based in Zurich. We bring a Swiss approach to engineering — careful, explicit and built to last — to organisations in Switzerland and internationally.

  1. 01

    Precision

    Clear requirements, explicit assumptions, measurable outcomes.

  2. 02

    Reliability

    Systems designed to be operated, monitored and maintained.

  3. 03

    Security

    Least-privilege access and secure defaults from the first commit.

  4. 04

    Privacy

    Data minimised, processed deliberately and kept under your control.

  5. 05

    Quality

    Reviewed code, tested behaviour and evaluated AI output.

11Responsible AI

Innovation with control.

Enterprise AI has to be governable. We design controls into the system from the first architecture decision — not as an afterthought.

  • Secrets, networks and models are protected with secure defaults and least-privilege access.

  • Personal and confidential data is minimised, masked where possible and never used beyond its purpose.

  • Every AI system has an owner, documented purpose, data inventory and review cycle.

  • People approve high-impact actions and can always see why the system acted.

  • AI inherits existing permissions — users only reach information they are entitled to.

  • Quality, cost and behaviour are measured continuously, with alerts when they drift.

SECURITYPRIVACYGOVERNANCEHUMAN OVERSIGHTACCESS CONTROLMONITORINGAI

12Working with CLEEV

Start where you are.

Some organisations begin with a single workshop, others with a defined build. Every stage stands on its own — and leads naturally to the next.

  1. Stage 01

    AI Discovery

    Understand opportunities.

    You receivePrioritised use-case map and readiness assessment.

  2. Stage 02

    Proof of Concept

    Validate the idea.

    You receiveA working prototype on your data, with evaluation results.

  3. Stage 03

    Project Development

    Build the production solution.

    You receiveA production system, documentation and handover.

  4. Stage 04

    AI Transformation

    Transform multiple business functions.

    You receiveRoadmap, platform architecture and delivery across teams.

  5. Stage 05

    Continuous Optimisation

    Improve deployed systems.

    You receiveMonitoring, evaluation and regular improvement cycles.

Enter at any stage

13AI Readiness Check

How ready is your business for AI?

Ten questions, about three minutes. Get an indicative score across five areas, the gaps worth closing first and a suggested starting point.

Start the check

Free · no sign-up · answers stay in your browser

Five areas

  1. 01Goals & strategy
  2. 02Processes
  3. 03Data
  4. 04Systems & technology
  5. 05People & governance

14FAQ

Questions, answered.

What organisations usually ask before starting an AI or software project with CLEEV.

01

What does CLEEV do?

CLEEV is an AI transformation and software engineering company based in Zurich, Switzerland. We design and build AI automation, AI agents, AI integrations, custom AI solutions, enterprise knowledge (RAG) systems and modern software for businesses.

02

Where is CLEEV located?

CLEEV is located at Höschgasse 62, 8008 Zurich, Switzerland. We serve organisations in Switzerland and internationally.

03

What is AI automation?

AI automation uses artificial intelligence to handle the parts of a business process that rule-based tools cannot, such as reading emails and documents, classifying requests and extracting data. CLEEV combines this with dependable workflow automation, validation and human approval for exceptions, so tasks like invoice processing or request routing run with less manual work.

04

What is an AI agent, and how is it different from a chatbot?

An AI agent completes multi-step tasks, while a chatbot mainly answers questions. An agent can search your knowledge, call approved tools such as a CRM, decide on next steps and act — within permissions you define, with approval steps and a full log of every action.

05

What is RAG (retrieval-augmented generation)?

Retrieval-augmented generation (RAG) lets an AI assistant answer questions from your own documents and databases instead of from what a model happens to remember. CLEEV builds RAG systems that respect existing access rights and cite the sources behind every answer.

06

Which AI models does CLEEV work with?

CLEEV works with models from OpenAI, Anthropic (Claude), Google (Gemini) and open-source LLMs. We design systems to be model-agnostic, so a model or provider can be replaced as the technology changes. These are technologies we build with, not partnerships.

07

How does an AI project with CLEEV start?

Most projects start with a short AI discovery to identify the most valuable use cases, followed by a proof of concept on your real data. Successful concepts move into production development and, if wanted, continuous optimisation. You can also start directly at any stage.

08

How does CLEEV handle data privacy and security in AI projects?

CLEEV builds controls into AI systems from the start: least-privilege access, existing user permissions, logging, human oversight for high-impact actions and ongoing monitoring. Systems are designed around your data protection requirements, including the Swiss Federal Act on Data Protection (FADP) and the GDPR where it applies.

09

Does CLEEV also build software without AI?

Yes. CLEEV engineers web applications, SaaS platforms, APIs, backends and system integrations — with or without AI components — built with typed code, automated testing and CI/CD.

10

How can I contact CLEEV?

You can reach CLEEV by email at hello@cleev.ch, by phone at +41 76 762 44 48, or through the contact form at cleev.ch/contact.

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