Webinar

AOSP on Intel x86: Enterprise Android Built for Control, Longevity, and ScaleAgéndalo en tu calendario habitual ¡en tu horario!

Martes, 24 de febrero de 2026, de 11.00 a 12.00 hs Horario de Ohio (US)
Webinar en inglés

As Android expands into revenue-critical edge systems, enterprises increasingly require platforms prioritizing control, stability, and long-term operability over consumer services. This has driven preference for AOSP-based Android on Intel x86, combining open Android foundations with x86's performance, serviceability, and lifecycle characteristics. Esper delivers the enterprise control plane making AOSP on Intel x86 viable at scale. Esper Foundation provides fully integrated Android for Intel x86, while Esper's end-to-end OTA infrastructure supports security updates and lifecycle management for any AOSP deployment on Intel x86, regardless of device maker or configuration. These capabilities give organizations a single pane of glass to provision, secure, update, and operate Android fleets across diverse hardware and environments. From factory enrollment and zero-touch provisioning to OS and application updates, policy enforcement, and in-field recovery, Esper enables Android devices to behave like durable infrastructure rather than disposable endpoints. Built on the same operational principles, Esper also supports Linux- and Windows-based systems on Intel x86, allowing consistent lifecycle management across heterogeneous edge environments. While Android remains the primary focus today, this broader OS support reflects long-term commitment to making Intel-based edge systems operable, secure, and maintainable. This session explores why enterprises standardize on AOSP on Intel for long-lived edge systems where control and lifecycle stability matter most, how Esper supports production deployments across retail, restaurant, payments, and industrial environments, and what managing Android as unified fleet requires. Attendees will understand how Esper and Intel enable enterprise-grade Android today while establishing stable foundation for AI-enabled edge workloads.

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