Dynamic Traffic Routing & Pathing

Optimize traffic routing and content delivery in real time based on current conditions or strategic parameters, such as speed, performance, and operational costs.

Energy Efficiency Optimization

Optimize NOC, data center and infrastructure power consumption dynamically based on network traffic, resource loads, and adverse conditions.

Incident Response & Field Service Optimization

Optimize operational rules, correlation engines, incident response, and field service dispatch to pinpoint disruptions and decrease downtime.

Network Design, Deployment & Support

Optimize network element placements, routing paths, physical resource allocations, and labor staffing/scheduling to minimize deployment costs and time.

Service Disruption/Network Threat Prediction & Detection

Adapt in real-time to changing network conditions and alert potential disruptions and threats using generative AI models trained on baseline network activity and past events.

Predictive Maintenance

Prevent system failures and proactively identify early warning signs of network traffic issues or infrastructure malfunctions with precision.

Demand Forecasting

Simulate various hypothetical scenarios and predict demand for spikes in network resources to inform incident response and resource allocation planning.

Predictive Maintenance

Simulate degradation and “black swan” events to provide early warnings and predict when network infrastructure is likely to fail or require maintenance.

Service Disruption Prediction

Predict disruptions based on traffic patterns, usage, customer behavior, and service life of network infrastructure components, adverse conditions, or anticipated intrusions

Fault Tolerant Sensing

Create a virtual, digital twin of a critical node, sensor, or other network element, and provide reliable, unbroken data in the event of a failure or disruption.

Simulations

Conduct massively scaled, hyper-complex simulations to test network performance under extreme conditions, including postmortem analysis and training.

Virtual Sensors

Create virtual sensors / inferred channels based on correlated data to substitute for actual nodes/ sensors in extreme or constrained environments or with missing or incomplete datasets

Analytics Assistant

Analyze and visualize data using a conversational LLM-powered virtual assistant. Compress the model to run it in constrained environments.

Incident Diagnostics

Extract invaluable insights from massively scaled support operations and tickets to uncover patterns and efficiently debug problems, enhancing network incident response.

Incident Response

Automate the execution of incident response countermeasures and remediation steps, with system-generated recommendations.

Model Compression

Significantly reduce compute, tokens, and IT resources required for LLM operation without sacrificing accuracy or expressability.