Industrial automation systems
Backing a team that makes heavy industry autonomous — deploying computer vision and real-time control systems in environments where traditional automation cannot operate.
The challenge
Heavy manufacturing environments — steel mills, chemical plants, paper production — rely on manual process control for operations too variable, dangerous, or complex for conventional automation. This creates safety risks, quality inconsistencies, and labour dependencies that limit throughput and profitability. Existing industrial automation solutions are designed for structured environments and fail in these conditions.
Our approach
The company has built an edge AI platform that combines ruggedised sensor arrays with real-time computer vision and predictive control algorithms. The system learns from operator behaviour, adapts to process variability, and progressively automates decision-making while keeping humans in the loop for edge cases. Deployment requires no changes to existing physical infrastructure.
The outcome
Rollouts across several production lines at Nordic manufacturers showed sustained throughput and quality gains, with operations continuing without safety incidents over extended periods — the kind of operational proof we underwrite before scaling scope.
Illustrative case narrative — not a statement about a specific live investment or audited results.
Grid-scale energy management
→Real-time optimisation platform for renewable energy distribution networks.