Cisco’s new predictive engine is a cloud-based (SaaS) service that uses AI and machine learning to anticipate network issues before they impact users. It continuously analyzes telemetry data from routers, switches, servers, and other infrastructure to spot patterns that typically lead to problems. The main goal is to help enterprises reduce unplanned downtime and outages, which can disrupt employee productivity, customer service, and revenue. Instead of reacting to incidents after they occur, IT teams can use this engine as a kind of holistic network watchdog that flags likely hardware issues, bandwidth spikes, and application configuration changes in advance and suggests how to fix them. Cisco has been building and testing this predictive capability for about two years and plans to make it available across its broader product portfolio. Early adopters such as Phillips 66, Schneider Electric, and the Adecco Group are already using it to save time and operational cost by addressing issues proactively rather than firefighting outages.

In day-to-day use, Cisco’s predictive engine plugs into your existing network and continuously collects telemetry data from multiple sources, including routers, switches, and servers. That telemetry can include connectivity metrics, quality-of-service indicators, traffic patterns, and other operational signals. Once integrated, the engine: 1) Aggregates telemetry data from across the organization. 2) Learns normal and abnormal patterns using a variety of AI/ML models. 3) Predicts potential user-experience issues, such as degraded performance or connectivity problems. 4) Provides concrete remediation options, so operators know what actions to take. The engine doesn’t just flag a risk; it also looks at connectivity and quality of service to plan alternative routes or configuration changes. Customers can choose how broadly to deploy it—starting with a subset of the network and expanding over time—so they can align adoption with their operational readiness and priorities.

Enterprises can expect several practical benefits from Cisco’s predictive network engine: 1) **Reduced unplanned downtime and outages**: By identifying likely failures or performance issues before they occur, IT teams can intervene early, which helps keep employees productive and customer-facing services available. 2) **More proactive operations**: Instead of relying mainly on alerts after something breaks, teams can move toward a self-healing, predictive operations model. The engine acts as a holistic watchdog that surfaces risks such as hardware degradation, bandwidth spikes, or app configuration drifts. 3) **Improved user experience**: Because the engine focuses on connectivity and quality of service, it can predict user-experience issues and recommend alternative paths or configuration changes to keep applications running smoothly. 4) **Operational efficiency and cost savings**: Early adopters like Phillips 66, Schneider Electric, and the Adecco Group are already seeing time and cost savings by reducing firefighting and manual troubleshooting. Over time, this can help organizations reimagine how they manage network growth and complexity. Cisco plans to extend this predictive capability across its product range, with more details expected at its Cisco Live! customer event, so enterprises can gradually integrate it into their broader network strategy.