AI Consultancy & Training
Practical AI consultancy, training and prototyping for manufacturing teams and industrial environments.
AI Grounded in Manufacturing Reality
AI in manufacturing is not about replacing proven automation systems. It is about extending what is already in place with data-driven insight where it genuinely adds value. The challenge is not technology itself, but knowing where it fits — and where it does not. Most manufacturing environments already generate vast amounts of data. The opportunity lies in turning that data into actionable understanding.
This consultancy bridges the gap between industrial automation expertise and modern AI and data methods. With deep experience on the plant floor — in PLC engineering, commissioning, and production support — the starting point is always the manufacturing process, not the algorithm. This means AI work is scoped to real problems with concrete results, not speculative technology projects.
Whether the goal is to train a team on AI fundamentals, explore production data for patterns, or build a proof-of-value for a specific manufacturing challenge, the approach is practical, transparent, and designed to deliver results that production teams can trust and act on.
“Start from the manufacturing problem, not the algorithm. If classical automation solves it, use that.”
AI is only introduced where it clearly outperforms existing methods.
What We Offer
AI Consultancy & Training
Workshops and consultancy for engineering and production teams to understand where AI adds practical value in manufacturing, and where classical automation remains the right choice. Adapted to the team's experience level and the plant's real challenges.
Data Analysis & Prototyping
Hands-on data work with production data: cycle time pattern analysis, bottleneck exploration, anomaly signal detection. Using Python and SQL to turn raw data into actionable insight, with clear visualisations that production teams can interpret.
AI Exploration & Proof-of-Value
Carefully scoped AI experiments from concept to proof-of-value. Each exploration starts with a defined manufacturing problem and is designed to demonstrate practical impact within real production constraints, before any larger investment.
Approach to AI in Manufacturing
- AI is introduced only where it clearly outperforms existing methods
- Every exploration starts with a clear manufacturing problem, not a technology solution
- Prototypes are designed to be testable and explainable to production teams
- Classical automation and deterministic control remain the baseline — AI extends, it does not replace
- Data quality and access constraints are addressed upfront, before modelling begins