Industrial autonomous intelligence
Causal and neuro-symbolic reasoning applied to industrial operations, split across edge and cloud. We contribute the reasoning architecture as an R&D partner.
- Industrial AI
- Multi-agent systems
- Causal reasoning
- Neuro-symbolic AI
- Edge–cloud orchestration
Project details.
The challenge
Industrial operations generate enormous quantities of data and very few situations that repeat exactly. Rule-based automation handles the repeating cases and stops at everything else; a purely learned model handles the variation but cannot be held to a safety envelope.
The decisions also have very different time budgets. Some must be made in milliseconds beside the machine; others can be made centrally with far more context.
Our approach
We contribute the reasoning architecture: specialised agents that hold objectives rather than scripts, coordinate with each other where their domains overlap, and validate their intended actions against explicit operating constraints before committing.
The reasoning is deliberately split across edge and cloud, so a decision is made wherever its latency, data-residency and safety requirements can actually be satisfied.