Physical intelligence
Cryal Core is developing modular edge intelligence that connects physical measurements with operating context.
Prototype 1 is in development. Integrated hardware is not yet validated.
The opportunity
Physical sensing.
Operating context.
Local processing.
Machine intelligence should not be reserved for new machines. We’re building a foundation for contextual intelligence across existing mechanical systems, including equipment without native monitoring.
Technology
Machine behavior produces measurable physical signals. Speed, load and installation conditions shape their interpretation.
Vibration describes mechanical response; electrical measurements describe a different aspect of machine operation.
We develop machine-specific references that account for the installation and supported operating states.
Our modular design places acquisition and signal processing close to the machine, with embedded intelligence as a development objective.
Physical measurements and operating context guide interpretation. Diagnostic and adaptive performance remain validation objectives.
Platform / Prototype 1
Prototype 1 defines a shared Context Core and dedicated sensing Pods.
Sensing and local processing are distributed by design, with interpretation and history assigned to the Core.
Application-specific configurations require their own integration validation.
Conceptual architecture / intended responsibilities
Shared context, interpretation and local analysis. History and integration are design objectives.
Each Pod has an independent relationship with the Context Core. The Electrical Context Pod is not required for every future deployment.
Research and development
Our development firmware includes vibration acquisition and signal processing. Controlled offline studies inform sensing choices and prototype engineering.
A change in vibration.
The operating state changes too.
Which reference is relevant?
Use a reference appropriate to the operating state and installation.
Electrical current provides operating information. Supply-quality assessment depends on the measured quantities and their location.
Research results are scoped to their experiments; field performance requires separate validation.
Applications
Two engineering development tracks connect the platform to practical monitoring needs.
Industrial systems
Industrial motors and rotating equipment.
Motors and rotating equipment provide the initial practical environment for Prototype 1 engineering and prospective validation. The focus is machine behavior in its operating context.
Prototype 1 development / validation focus
Marine systems
Marine-engine condition intelligence.
EngineGuard is our originating marine-engine development track, focused on retrofit installations and engines with limited native diagnostics.
Marine engines / retrofit focus
Both tracks share the Cryal Core platform. Validation and practical requirements guide their development.
Company / collaboration
Cryal Core is a research-led engineering venture building toward a modular edge platform for mechanical and electromechanical systems.
Industrial Condition Monitoring and EngineGuard are development tracks within that wider ambition. We prioritize compatibility with existing infrastructure and cost-conscious deployment.
Start a conversation
We welcome technical and industrial collaboration on sensing, integration and future applications.