Applications
EOS Max dispatches each event directly to the state that handles it - by priority, run to completion - so complex systems stay predictable under load and keep running for years. Built for robotics, industrial automation, medical devices, automotive, energy and infrastructure, and Edge AI.
// 01 · By sector
Systems now are more autonomous, more connected and more intelligent. And the hard problems underneath - coordinating events, states and timed events in real time - are more complex than ever. EOS Max is built to solve them.
Autonomous mobile robots, robotic arms, inspection and service robots, drones.
// The challenge
A robot juggles navigation, sensor fusion, motion control, fault handling, charging and safety behaviours at once - hundreds of interacting states and decision pathways.
// The fit
Each behaviour is modelled as its own virtual state machine and scheduled by event. Complex autonomy stays readable, deterministic and efficient, instead of buried in task threads and custom logic.
Machine controllers, PLC-class control, actuators, production-line coordination, safety systems.
// The challenge
Industrial systems coordinate sensors, actuators, safety events, machine states and production logic - and they have to stay deterministic across long deployment lifecycles.
// The fit
Event-driven processing keeps response times predictable while cutting architectural overhead. Behaviour is captured as state machines that are straightforward to maintain years after delivery.
Infusion and delivery devices, diagnostic and monitoring equipment, handheld and wearable instruments.
// The challenge
Regulated, safety-critical devices need behaviour that is traceable, validated and unambiguous - from first specification through to the evidence a certification needs.
// The fit
Behaviour is bounded and explicit, and every requirement carries a unique identifier into generated code and tests. The traceability and evidence build up as you go, not reconstructed before an audit.
ECUs, body and comfort control, sensor and actuator modules, sub-system controllers.
// The challenge
Vehicle software is safety-critical, runs across long platform lifecycles, and has to stay predictable as features are added over time.
// The fit
Deterministic, event-driven control with a small, controlled footprint. State machines keep behaviour clear across evolving platforms, and traceability supports the assurance these systems demand.
Battery energy storage, EV charging, solar and grid-interface controllers, protection and monitoring.
// The challenge
Energy installations need predictable control across battery states, charging, discharging, grid interaction, protection events and maintenance modes - in mission-critical, long-lived environments.
// The fit
Deterministic event handling makes state transitions reliable and responsive, while the small footprint suits controllers that run for years in the field.
Smart sensors, vision and audio devices, autonomous and connected products running local inference.
// The challenge
Edge-AI devices combine local inference, sensor events and deterministic control - and they have to do it on constrained, low-power hardware without leaning on the cloud.
// The fit
EOS Max coordinates inference, sensor events and control on one device. AI outputs become event-driven state transitions that run reliably and efficiently, with deterministic behaviour around the model.
// See it work
See a reference project get built from specification to code architecture.