Case Study: Larger Enterprise Networking Company achieves greater predictability and efficiency with CSS Corp’s AI-powered Early Warning System

Driving Predictability and Optimization in Network Operations Through

Larger Enterprise Networking Company, a provider of enterprise-grade networking solutions, was struggling to manage rapidly growing technical support operations as ticket volumes climbed to 20,000 per month. Manual processes and traditional automation were not enough to handle the complexity of enterprise support, making it difficult to prioritize cases, assign the right engineers, and maintain SLAs and customer satisfaction.

CSS Corp implemented an AI-based Early Warning System (EWS) using AI, ML, NLP, intelligent automation, and contextual knowledge management. The solution ingested data from calls, CRM records, emails, and chats to predict time-to-resolve, classify and prioritize cases, and support skill-based routing through real-time dashboards. CSS Corp reported several hundred thousand dollars in savings, more than 35% improvement in time to resolve, 10–13% improvement in CSAT, 25% better engineer performance, and automated handling of 100% of ticket allocation with 40% of call volumes managed without manual intervention.