Reduce downtime by using our ML models to analyze IoT sensor data to predict equipment failures before they happen, enabling timely maintenance and reducing costly downtime & potential safety risk incidents. Learnt patterns over a period helps you understand and guide you through potential pitfalls like problematic devices, longevity, vulnerabilities, health issues, etc.

Every time you onboard a device, our platform learns. As you deploy similar types of devices, our platform guides you on what configuration settings to use & suggests relevant templates. In addition, we provide insights into key KPIs for your operations like MTTR, MTBF, across your global footprint and at each device level.

Smart Energy Management: AI algorithms monitor and optimize energy usage across edge devices, identifying inefficiencies and providing actionable insights to lower energy costs. Assess patterns in edge device usage to optimize the deployment and utilization of your assets, leading to better resource management
and cost savings.

Identify anomalies, incidents & health parameters for every edge endpoint with remote diagnosis. Automate actions & healing through remediation actions that allows the devices to heal & bounce back to peak performance conditions. Build workflows (or integrate into existing workflows) to ensure that healing happens when all conditions are met. Automate your operations based on real-time data from your edge devices thereby improving efficiency and minimizing human intervention.

Rollout proactive threat detection mechanisms to detect & respond to unusual patterns, threats, vulnerabilities & deviations. Ensure comprehensive asset and metrics monitoring, and gain visibility into actions that could lead to compliance & regulations violations. Leverage your Edge endpoints to maintain continuous compliance & regulatory needs.