Esper builds mobile device management and custom OS solutions for dedicated-device fleets (POS systems, logistics hardware, healthcare devices). The stack—Python, Go, TypeScript, Kotlin, Android/iOS SDKs, plus Kafka and gRPC for fleet orchestration—reflects an engineering-first organization focused on real-time device control at scale. Active hiring is heavily weighted toward senior engineering (16 of 26 open roles), signaling investment in backend infrastructure and agent-level reliability rather than sales expansion.
Esper provides device management and OS customization for enterprises running dedicated hardware fleets across retail, logistics, and healthcare verticals. The platform automates provisioning, fleet updates, and device monitoring while eliminating manual re-provisioning workflows. Product surface includes Android/iOS MDM, a custom Android Foundation layer (AOSP-based), backend services for device-to-cloud communication, and web-based fleet dashboards. Founded in 2018 and based in Bellevue, the company operates with a 51–200-person team, primarily in the United States and India.
Core languages are Python, Go, and TypeScript. Infrastructure: AWS, GCP, Azure with Kubernetes and Docker. Device layer: Android SDK, Kotlin, iOS, custom Android (AOSP, Yocto, OpenEmbedded). Messaging: Kafka, MQTT, gRPC. VNC and WebRTC for remote device interaction.
Active projects include AI-assisted development tools, a custom Esper Foundation for Android, device management platform UI, Android agent/SDK improvements, device interaction backends, web dashboards, and device validation processes. Also piloting early products and accelerating reseller implementation workflows.
Esper's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.