See and act on every mission critical asset, down to the serial number

Peaxy Ontology runs in the cloud or fully air-gapped and is responsible for the integrity and security of the data it holds, at rest and on the wire. A schema engine handles the semantics and resolves all ingested data — whether telemetry, test benches, manufacturing execution data or maintenance records — accurately to the serial number.

Each serial number under management thus gets structure, relationships and context that weave it into the asset hierarchy and connect every stage of its lifecycle in one continuous thread. PLI currently serves more than 550,000 serialized assets and 25.1 billion data points this way. The data model is explicit, so engineers and AI agents inspect the same ontology. Every asset is intelligible and anchored in the physical world, with its state and history a query away.

Peaxy Constellation is a set of modular, configurable applications, tools and services for data ingestion, processing, validation, access, visualization, control and action. Every read and write passes through Peaxy Ontology, so its semantic rigor carries through every application. A deployment is configured to the organization, the roles of the people using it and the phase of the asset lifecycle it serves.

Two classes of components do the work: Deterministic, headless pipelines cleanse and validate incoming data and run the periodic calculations and analyses an operation depends on. Modules give people the interface for oversight and control: live and historical monitoring, capture of manufacturing and lifecycle events, forensic investigation of an asset’s history, alert and report management, statistical process control on the line, and regulatory records such as the battery passport. Timeline and tabular views stay responsive at every scale, from a single unit to an entire fleet.

Users configure Peaxy AI agents to run continuous monitoring, produce periodic reports and generate new, semantically rich data that flow back into the platform for downstream use.

Skills merge Peaxy’s procedural subject-matter knowledge with AI analysis and apply both to the organization’s own knowledge base. Use cases can include explaining the repair procedure for the unit in question, extracting energy savings from a load profile, identifying data hygiene gaps, or triaging competing alert severities.

Experts are intent-based agents that take the initiative, watching for drift from normal operating conditions and recommending the next action. Use cases include continuous condition-based maintenance, predictive maintenance scheduling, systems optimization, and lifecycle extension. Every recommendation arrives with its evidence attached.