A Swiss engineering company Over twenty years in business
Engineering software that has to keep working.
Artabel is a Swiss engineering company. We build information systems, industrial instrumentation and applied AI for industry, healthcare and cultural institutions. Our oldest system has been in daily production at an aluminium plant since 2008.
Where our systems run
What we do
Four areas of work.
Artabel covers both the modelling and the engineering that puts it into service — integration, access control, release, and the years of maintenance afterwards.
Applied AI
Retrieval and document intelligence, computer vision, speech and structured extraction, predictive modelling, data-centric AI.
Enterprise software
Configurable workflow and information systems with role-based access, approvals, reporting and analytics, built to be maintained for a decade.
Systems integration
Connectors, APIs, data pipelines, migration and deployment into estates that were never designed to be connected.
Instrumentation & 3D
Sensing and smart devices in hostile environments, real-time tracking, plus 3D visualisation and immersive interfaces.
Research projects
Engineering in funded research.
Artabel contributes software engineering and systems integration to European research projects.
Method
Evaluation before release.
AI systems are evaluated against task-specific criteria agreed with the client. The evaluation typically includes a relevant baseline, representative test material and review by someone qualified to judge the output.
How we work
Scope, prototype, validate, implement.
Four stages, each ending in a decision you can act on: whether the data supports the task, whether a prototype behaves, whether the measurement holds, and whether the system is ready to run in your environment.
Sectors
Sectors we work in.
Medical AI and MedTech
Imaging and multimodal interpretation, clinical decision support, and structured documentation from consultation audio.
Industrial AI
Predictive maintenance from sensor streams, anomaly detection, and measurement in conditions that damage ordinary instruments.
Agriculture and agri-food
Crop and quality monitoring, multimodal sensing, and decision support for producers.
Culture, heritage and public knowledge
Source-grounded interpretation for museums and archives, rights-aware access, provenance and multilingual access.
Next step
Tell us about the task.
Describe the problem and the constraints around it, and we will come back with how we would approach it.