Intelligence at the core, not on the surface.
Artificial intelligence is not a feature we add — it is the foundation we build on.
[01] OVERVIEW
Our platforms use AI to do what would be impossible, impractical, or prohibitively expensive to do manually. From interpreting visual data to synthesising public records into scored assessments — every system we build is designed to think, evaluate, and act autonomously.
[02] FEATURES
Computer Vision
Analyse images, match visual patterns, and verify identity across platforms based on physical structure, not metadata.
Data Intelligence
Aggregate and correlate data from dozens of public sources to build a comprehensive picture from scattered, unstructured information.
AI-Powered Analysis
Interpret raw data through AI models that read, evaluate, draw conclusions, and produce structured assessments in natural language — in multiple languages.
Automated Scoring
Weigh multiple dimensions simultaneously to produce a single, interpretable result: a score, a grade, a recommendation. In seconds, not hours.
Process Automation
Execute complex, multi-step workflows end-to-end — from data collection to finished result — without human intervention.
Real-Time Monitoring
Continuously scan public sources for changes and trigger alerts immediately when something relevant happens.
[03] HOW IT WORKS
Analysis & Concept
We analyse your processes, identify AI potential, and create a detailed implementation concept.
Prototype & Validation
A functional prototype is tested with real data, iterated, and validated for practical use.
Production & Scaling
The validated solution is deployed to production, monitored, and continuously optimised.
[04] FAQ
Which AI models do you use?
We work with leading language models, computer vision models, and specialised open-source models — depending on the use case and requirements for data privacy and accuracy.
How accurate are the AI analyses?
Algorithms don't make careless mistakes. They apply the same rigour to the ten-thousandth analysis as to the first. Accuracy improves continuously as the data grows.
Where is the data processed?
By default in Switzerland. Our systems are built for data protection and long-term stability. On-premise solutions are available on request.
How long does a typical AI project take?
An initial prototype is ready in 2–4 weeks. Production implementation takes 2–4 months depending on complexity, including testing and optimisation.