Applied AI for industrial processes and systems
We integrate AI where it can help solve a specific task: interpreting images, querying documents, classifying information or detecting patterns. We review data and constraints before selecting models and connecting them to your systems.
The problem
A demo can work well and still be far from operational requirements. Data, integrations, response times and how errors are evaluated determine whether a model is useful.
What we do
- Document queries using RAG, data preparation and references to source material.
- Prediction and classification models (sales, demand, anomaly detection).
- Custom NLP and deep learning when the case justifies it.
- Computer vision applied to industry and robotics: inspection, quality control, defect detection and robot guidance.
- Comparison of alternatives and testing against criteria agreed before development.
Technologies
Python · PyTorch · Transformers · Computer vision (OpenCV) · RAG · RPA · LLMs.
Who it's for
Teams with a defined task that need to assess how AI can fit into their process.
Related project
NLP detection and classification with transformer models for a client in the education/research sector.
Frequently asked questions
- Generative AI or classic automation?
- The choice depends on the task and data. We compare rules, automation, supervised models and generative models in terms of accuracy, cost and maintenance.
- Is my data safe?
- Together, we define which data the system can use, where it is processed and who can access it. Private deployment can be included according to project requirements.
- Is this eligible for grants?
- Some projects may fit public funding programmes. Eligibility depends on the current call and the circumstances of the company and project.