AI-Powered Code Modernization Platform with Anthropic Claude
Pragma Edge AutoModernAI is an AI-Powered Code Modernization Platform powered by Anthropic Claude that helps enterprises modernize legacy applications, automate transformation workflows, accelerate cloud-native migration, and enable…
AI-Powered Code Modernization | Anthropic Claude | Automated Transformation
AI-Powered Efficiency for Modern Data Centers
Condition-Based Maintenance
Single System of Record
Visibility Across Facilities & IT
NOC-Integrated Uptime
One Platform, Five Ways to Take Control
Click a capability to see how it applies to your data center operations.
Asset Management
Apply AI-driven insights to streamline asset workflows so technicians can work faster, reduce downtime, and maintain compliance across every facility in your portfolio.
Asset Performance Management
Use real-time, AI-powered asset health insights to boost uptime and enable condition-based maintenance instead of reacting after equipment fails.
Facilities Management
Optimize space, energy, leases, and facility operations in one unified solution instead of juggling separate point tools.
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Relevant to Every Data Center Stakeholder
One system instead of five
Replace multiple point solutions with a single, unified platform spanning both IT and facilities operations, so your team stops reconciling data across disconnected tools.
SUSTAINABILITY & ESG TEAMS
Reporting that writes itself
Benchmark energy performance and automate GHG and climate-reporting data collection, instead of manually assembling numbers from siloed systems each quarter.
OPERATIONS & NOC TEAMS
Continuity you can prove
Integrate asset health data directly with NOC alarms for automated emergency response, so outage continuity is backed by real-time visibility, not guesswork.
Works Within Your Existing Ecosystem
Maximo connects into the systems you already run, so adoption doesn’t mean ripping anything out.
Let's Build Your AI-Ready Data Center
Do you have a question for our specialists, want to discuss your requirements, or learn more about our expertise? Feel free to send your request using the form below.
Apply maximo asset operations to a defined use case.
Connect facilities and asset signals to a reviewed maintenance or operating decision. Define the relevant data-center dependencies so an AI-assisted recommendation can be assessed in its service context.
Define the engagement scope.
Start with the asset hierarchy, work-management process and information needed by planners, technicians and operating teams. Review how inspection findings, condition signals, maintenance history and work orders are connected in the selected Maximo environment. Define the application scope and integrations before choosing configuration or customization changes.
Validate the operating result.
Validate the complete path from an observed condition to an authorized work action. Include incomplete asset data, duplicate notifications, material availability, mobile connectivity and supervisory review. Predictive or AI-assisted recommendations should provide evidence for the responsible person; their use does not remove operational approval or maintenance accountability.
Prepare for a focused working session.
Bring the asset register, representative work orders, current Maximo deployment details, integration list and maintenance priorities. Agree the pilot population, data-quality checks and acceptance scenarios. Deliverables can include the process design, configuration scope, integration requirements and support handover, with responsibility assigned for ongoing asset-data quality.
Make the next step specific.
Bring your operating context, priorities and questions. We’ll help identify the relevant next step.
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