AI-powered mobility performance optimization continuously analyzes usage patterns, carrier performance, and device health across your mobile fleet — automatically identifying and acting on optimization opportunities that no manual review process could match at enterprise scale.
Enterprise mobile fleets of thousands of devices generate usage data that is simply too large for manual analysis. AI performance optimization processes this data continuously — surfacing the rate plan mismatches, underperforming carriers, and device configurations that cost money and reduce productivity.
Every engagement follows a structured process — from discovery and vendor evaluation to pilot design and scale — adapted to the specific constraints and maturity of your organization.
We establish a comprehensive baseline of your mobile fleet performance — usage patterns, carrier performance by geography, device health distribution, and cost per user segment — identifying the optimization opportunities with the highest potential impact.
We evaluate AI-enabled mobility management platforms — Tangoe, MOBI, Calero, and others — against your fleet size, carrier mix, MDM platform, and optimization objectives.
We design the carrier performance monitoring framework — signal quality by location, data throughput benchmarks, reliability scoring — that feeds continuous optimization decisions and informs carrier contract renegotiations.
We design the automated optimization workflows — rate plan adjustments, carrier switching recommendations, device replacement triggers — with appropriate approval gates for changes above defined thresholds.
These are the evaluation dimensions that consistently separate successful deployments from expensive pilots that never reach production scale.
Meaningful performance optimization requires data on every device, every carrier, and every usage pattern. Evaluate how comprehensively the platform covers your specific device types, MDM platforms, and carrier APIs.
AI optimization recommendations that are frequently overridden erode trust and add management overhead. Evaluate recommendation accuracy and the false positive rate for suggested optimizations.
Real-time carrier data — usage, performance, plan details — requires direct carrier API integration. Evaluate the breadth of carrier integrations and the freshness of the data they provide.
Performance optimization must integrate with your MDM platform to correlate device health, app performance, and configuration data with usage patterns. Evaluate integration with your specific MDM (Intune, Jamf, VMware Workspace ONE).
Automated plan changes affect employee devices. Evaluate the approval workflows, notification processes, and rollback capabilities that prevent optimization actions from disrupting employee productivity.
Performance optimization value must be demonstrated continuously. Evaluate reporting capabilities that quantify the optimization actions taken and the savings or performance improvements achieved.
"RLM brought structure to a process we didn't know how to start. They asked the right questions, surfaced the right vendors, and kept us from making decisions we would have regretted."
"What set RLM apart was that they didn't have a preferred answer. They evaluated our options honestly and told us what they actually thought."
Start with a no-cost conversation with an RLM AI advisor — vendor neutral, no agenda, just clarity.
Speak to an Advisor