WAN Path Optimization

Problem Statement

Enterprise WAN environments connect branches, data centers, cloud workloads, and remote users over multiple transport types, including MPLS, broadband internet, and cellular links. Traditional routing protocols select paths based on static cost metrics rather than real-time application performance. As SaaS, video collaboration, and cloud-native applications dominate traffic, suboptimal path selection increases latency, packet loss, and user complaints. Network teams often lack predictive visibility into path degradation, leading to reactive rerouting and inefficient use of available bandwidth.

AI Solution Overview

AI-driven WAN path optimization continuously evaluates transport performance, application sensitivity, and historical traffic trends to dynamically select the most efficient and reliable path for each session. Machine learning models analyze latency, jitter, packet loss, and congestion patterns to predict degradation and reroute traffic proactively.

Core capabilities

These AI capabilities enable intelligent, application-aware path control across hybrid WAN environments.

• Real-time path performance modeling: Continuously assess transport quality metrics across MPLS, broadband, and cellular links.
• Application-aware routing decisions: Match application requirements, such as low latency or high throughput, to the most suitable path.
• Predictive degradation detection: Identify early signs of ISP instability or congestion before user impact occurs.
• Dynamic traffic steering: Automatically shift sessions to alternate paths when performance thresholds are forecasted to be breached.
• Continuous learning optimization: Refine routing models based on historical outcomes and evolving traffic patterns.

Together, these capabilities improve application reliability while maximizing the value of existing WAN investments.

Integration points

Effective path optimization requires interoperability across WAN and monitoring systems.

• SD-WAN controllers: Integrate with Cisco SD-WAN, VMware SD-WAN, or similar platforms for centralized routing policy enforcement.
• Network performance monitoring tools: Connect with ThousandEyes or Catchpoint for internet path visibility and SaaS performance insights.
• Cloud networking platforms: Interface with AWS, Azure, and Google Cloud to optimize hybrid cloud connectivity paths.
• Observability and ITSM platforms: Feed routing events into Splunk, Datadog, or ServiceNow for monitoring and governance.

Integrated visibility ensures optimized routing decisions align with operational oversight and compliance standards.

Dependencies and prerequisites

The following foundations are essential for success.

• Granular link telemetry: Continuous measurement of latency, jitter, packet loss, and throughput across all transports.
• Application performance mapping: Clear understanding of application sensitivity and business priority tiers.
• Programmable WAN infrastructure: API-enabled SD-WAN or routing platforms capable of dynamic traffic steering.
• Defined performance policies: Established thresholds and SLAs that guide automated path decisions.

These prerequisites ensure WAN optimization remains controlled, predictable, and aligned with business requirements.

Examples of Implementation

Multiple industries apply AI-driven WAN path optimization to maintain service quality across distributed operations.

• Financial services: Dynamically route digital banking and trading traffic over the lowest-latency paths during peak transaction periods, while redirecting noncritical batch workloads to secondary links.
• Healthcare systems: Optimize telehealth video sessions and EHR access by automatically steering traffic away from congested ISP routes.
• Retail enterprises: Route point-of-sale and inventory traffic across the most stable links during seasonal demand surges, minimizing transaction delays.

These implementations demonstrate how predictive routing intelligence improves resilience and user experience without requiring constant manual intervention.

Vendors

Several startups are advancing AI-driven WAN optimization and intelligent routing capabilities.

• Graphiant: Provide Network-as-a-Service with intelligent, policy-based traffic steering across a global edge fabric. (Graphiant)
• Aryaka: Deliver managed WAN and SD-WAN services with performance optimization across a private global backbone. (Aryaka)‍
• Alkira: Offer cloud-native networking with centralized policy orchestration and programmable traffic routing across hybrid environments. (Alkira)