From research to application.
We research problems that come from the field, test them with prototypes and turn validated solutions into working systems.
We go deep in three technology areas.
Our AI and machine vision R&D comes together on a solid software architecture.
Language Models and Automation
We work on knowledge retrieval, source attribution and approval-based automation flows so that large language models can run safely on an organisation's own knowledge.
- Knowledge retrieval with sources
- Structured information extraction from documents
- Agents that work with permissions and approval steps
Computer Vision
We develop imaging set-ups, lighting and analysis methods for surface defect detection and camera-based measurement on continuous production lines.
- Camera and lighting design
- Surface defect detection and classification
- Dimensional checks and reporting
Software Architecture
We design scalable, maintainable architectures that integrate with existing systems, so research results can run reliably in the field for years.
- Modular, maintainable structure
- Integration with existing systems
- On-premise and private cloud compatibility
Research → Prototype → Validation → Application
We mature every idea step by step until it is proven to work in the field.
- 1
Research
We examine the problem, the state of the data and possible methods together.
- 2
Prototype
We build a small, fast prototype that tests the riskiest assumption.
- 3
Validation
We validate the prototype with you under real or near-real conditions.
- 4
Application
We turn the validated approach into a maintainable product or system.
Technology shaped by field requirements.
Our solutions start not in the lab but with real needs on production lines and in office processes.
- Problem definition starts in the field
- Measurable acceptance criteria are set together
- Results improve with user feedback
