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Automate the manual steps, keep the decisions

We look at a process with your team and classify every manual step. What is worth it, we build and then operate hand in hand with our platforms.

Illustration: documents go to the AI. It turns them into a suggestion that a person checks.

Approach

What we leave to the AI

We break your process down into individual manual steps and assign each one to one of three levels. What counts is how much responsibility a step carries.

Abstract graphic: a green ring of light with a bright point making its rounds.

Automation handles it

If the result is unambiguous, a fixed rule or an interface is enough: passing data on, matching values, monitoring deadlines. This needs neither AI nor approval; it just runs.

Abstract graphic: a cyan spark from which a straight line of light leads to the top one of three fields and lights it up.

AI prepares

Where something has to be read, summarised or classified, the AI makes a draft. A person checks it and accepts, changes or discards it.

Abstract graphic: a violet line of light that splits into two paths at a bright point.

A person decides

Anything that concerns people, money, health or the law is decided by a person. The AI prepares, but it does not conclude. Where this line runs, we define with you.

How Smart-Extrakt works at OPAN®

Delivery notes or prescriptions often arrive as a PDF, scan or mobile phone photo, and someone types in the details. That takes time, and mistakes are often only noticed once the work is already under way. At OPAN® the AI has been reading attached documents since summer 2026.

  1. The document arrives

    OPAN® is the platform for referrals to outpatient and inpatient aftercare organisations. The user uploads the document or pastes it from the clipboard, text PDFs just like photos.

  2. The AI reads it

    Smart-Extrakt passes the document to the AI on our dedicated high-performance hardware including GPUs. For photos, the model first recognises the writing, then the meaning, and maps the details to the form fields.

  3. The details are ready

    This runs in the background while the user carries on working. The values appear in the form as a suggestion, and in the sidebar one click shows which part of the document a field comes from.

  4. A person has the last word

    Every suggestion can be checked, accepted or discarded individually. Only what a person confirms goes into the form, and the log records what was accepted.

Screen recording from OPAN®.

Getting started in three steps

It starts with tasks that keep recurring in your team. We begin with one of them and only expand once it works in everyday use. That way, after every step you know what it delivers and what the next one costs.

  1. Initial consultation

    Free of charge and online, 30 to 60 minutes. You bring up to three tasks, ideally together with a person who works with them every day. Together we choose one.

  2. Workshop on optimisation potential

    Half a day, on site or on screen, quoted based on effort. We go through the task with the people who do it, map the data flow and assign every manual step to a level.

  3. Small start

    At first, a few people work with the solution and give us feedback. On request, we show a clickable prototype beforehand.

What you get after the workshop

  • A sketch of the process, today and after implementation
  • Every manual step classified: automation handles it, AI prepares or a person decides
  • An integration plan: systems, data, leading source, permissions
  • A reasoned recommendation, even if it is ‘no AI’
  • An estimate for implementation and operations

Good to know

  • We discuss the result in one hour with management and the team
  • For personal or health data, we agree beforehand how we protect it: depending on the case, anonymised, with a non-disclosure agreement or a data processing agreement

Connecting AI to existing systems

The data for a task is usually already somewhere: in the ERP, in the CRM, in a specialist application or in an Excel list. The stack fetches it via interfaces and brings it together. Permissions per role control who may see what.

Example of a customer API with OpenAPI documentation: three endpoints for reading and writing, secured with OAuth2.

Interfaces

REST endpoints with OpenAPI documentation, secured with OAuth2. This is how we connect the systems in which your data lives today.

Data from ERP, CRM and an Excel list flows into a cleaned customer database: duplicates removed, fields standardised.

Bringing data together

We clean data from several sources and bring it to where your team needs it. This is how the platforms of Swiss-Ski and the Swiss Hiking Trail Federation work.

An assistant uses the MCP access to answer the question of which registrations are still awaiting approval. It only has read permissions.

Your assistant via MCP

The stack and Stack CMS come with MCP access, the open standard for AI assistants. Through it, your assistant looks into content and data and carries out tasks, with exactly the permissions you give it.

Operations

We run the AI

We rely on open AI models so that the AI stays independent of individual providers and their terms. The market for them moves fast. We monitor it continuously, test new models and use them in your applications. We handle operations within the same ISO/IEC 27001 certified framework as for our platforms.

  • Processing on dedicated hardware in Switzerland, without passing data on to external AI providers.
  • Inference instead of training: the model calculates an answer from your request and learns nothing from it. Requests are then discarded and are not used for any analysis or training.
  • Isolation according to protection needs: how strongly the systems are sealed off depends on your requirements and the sensitivity of the data.
  • Specialised models: a large model can do almost anything, a specialised one does its job faster and makes running it on our own hardware affordable. That is why, depending on the use case, we use models for text and translation, for images and documents, for spoken language or for following instructions precisely.
  • Traceable: every step an agent takes is logged, from the task to the result. This makes it possible to spot faulty behaviour, find its cause and prevent it in future.
Operations view in the cloudtec Stack: a language model and text recognition run via a shared interface on dedicated hardware in Switzerland. Today the language model was switched from version 3 to 4, tested in advance and implemented for the application. A card confirms: hardware in Switzerland, no passing on to providers, no training with your data, ISO/IEC 27001.
Our stance

AI lightens the load, people decide

We build AI for tasks your team would like to hand over. It does what would otherwise be left undone. What follows from it is decided by a person.

What AI and interfaces take over

  • Reading details from documents
  • Writing drafts of reports and summaries
  • Analysing and interpreting data
  • Matching data between systems and passing it on

What stays with your team

  • Confirming what the AI has prepared
  • Deciding on details concerning people, health or money
  • Talking to clients and patients
  • Choosing what to make easier next
Questions from management

What you want to know before the first step

What does getting started cost?

The initial consultation is free of charge. We then quote you for the workshop on optimisation potential based on effort, so you know the price before you commit.

Where is the data processed?

On dedicated high-performance hardware including GPUs in Switzerland, within the same ISO/IEC 27001 certified operations as our platforms. The hardware does not send any data to the internet of its own accord. If you connect an external assistant via MCP, the data it queries goes to that assistant’s provider.

Does a model learn from my data?

No. We run open models and do not train them, neither with your data nor with any other data.

What is stored?

The models process requests without storing them. Data is stored only in the platform itself, according to its usual retention rules. With Smart-Extrakt, OPAN® records which details were accepted.

Does my team have to use the AI?

We decide that with you for each project. At OPAN® , for example, each organisation activates Smart-Extrakt itself. Anyone who does not use the feature fills in the form as before.

Who owns the code and settings?

We settle this depending on the client and project, in the contract before implementation. This covers the code, the configuration and the instructions to the model.

Case studies

In use with our clients

Three platforms on which AI or an interface takes over manual steps today.

Which AI optimisation shall we tackle first?

Tell us what you need. We will be happy to look into it and arrange an appointment with you for the initial consultation.