Let's connect ↗Bring remote condition information into asset-management workflows with consistent identities, useful alerts and a defined response path.
Asset programs are connecting inspection, condition signals and AI-assisted insight with work management. The difficult handoff is often between finding a problem and getting the right person to act with the right context.
Pragma Edge organizes asset work around See, Listen, Think and Act. We connect asset data, inspection evidence, monitoring and prioritization with planning and field execution, choosing the scope that fits the customer environment.
Start with a representative asset class and a maintenance journey. Validate data quality, agree when an observation warrants action, and review whether the resulting work improves the operating process before expanding coverage.
Associate approved readings and inspection information with the correct asset.
Identify stale observations and relevant operating conditions before triggering a response.
Give planners the evidence needed to decide whether investigation or field work is appropriate.
Review sensor sources, asset identifiers, signal quality and monitoring thresholds. Define how abnormal conditions become an investigation, inspection or maintenance request.
For Maximo Remote Asset Monitoring, focus the engagement on connect remote observations, evaluate signal quality, coordinate maintenance review. Agree acceptance evidence for each workstream with its business and technical owners.
Baseline the measures relevant to your engagement, then compare results through implementation and operation.
A remote equipment signal changes; the team reviews its operating context and data quality before dispatching a technician.
Use your current environment, a representative workflow and its exceptions to define the work. Confirm the supported versions, integration boundaries, acceptance criteria and delivery responsibilities before implementation.
Discuss your environment →Explore the related technology and its role in your business process.