Cisco wanted to scale its digital help engineer that assists its technical help groups around the globe. By leveraging its personal Splunk know-how, Cisco was in a position to scale the AI assistant to help greater than 1M circumstances and unencumber engineers to focus on extra complicated circumstances, making a 93+% buyer satisfaction ranking, and guaranteeing the crucial help continues operating within the face of any disruption.
For those who’ve ever opened a help case with Cisco, it’s seemingly that the Technical Help Heart (TAC) got here to your rescue. This around-the-clock, award-winning technical help crew providers on-line and over-the-phone help to all of Cisco’s clients, companions, and distributors. Actually, it handles 1.5 million circumstances around the globe yearly.
Fast, correctand constant help is crucial to guaranteeing the shopper satisfaction that helps us keep our excessive requirements and develop our enterprise. Nonetheless, massist occasions like crucial vulnerabilities or outages can trigger spikes within the quantity of circumstances that slow response occasions and shortly swamp our TAC groups, impressioning buyer satisfaction in consequence. we’ll dive into the AI-powered help assistant that assists to ease this challenge, in addition to how we used our personal Splunk know-how to scale its caseload and enhance our digital resilience.
Constructing an AI Assistant for Help
crew of elite TAC engineers with a ardour for innovation set out to construct an answer that would speed up challenge decision occasions by increaseing an engineers’ skill to detect and remedy buyer issues. the was created — it’s greater than an AI bot and fewer than a human, designed to work alongside the human engineer.
Fig. 1: All circumstances are analyzed and directed to the AI Assistant for Help or the human engineer primarily based on which is most applicable for decision.
By immediately plugging into the case routing system to research each case that is available in, the AI Assistant for Help evaluates which of them it may well simply assist remedy, together with license transactions and procedural issues, and responds on to clients of their most well-liked language.
With such nice success, we set our eyes on much more help for our engineers and clients. Whereas the AI Assistant for Help was initially conceived to assist with the high-volume occasions that create a big inflow of circumstances, it shortly expanded to incorporate extra day-to-day buyer points, serving to to scale back response occasions and imply time to decision whereas persistently sustaining a 93+% buyer satisfaction rating.
Nonetheless, as using the AI Assistant grew, so did the complexity and quantity of circumstances it dealt with. An answer that when dealt with 10-12 circumstances a day shortly ballooned into tons of, outgrowing the methodology initially in place for monitoring workflows and sifting by log knowledge.
Initially, we created a technique generally known as “breadcrumbs” that we tracked by a WebEx area. These “breadcrumbs,” or actions taken by the AI Assistant for Help throughout a case from finish to finish, have been dropped into the area so we may manually return by the workflows to troubleshoot. When our assistant was solely taking a small quantity circumstances a day, this was all we would have liked.
The issue was it couldn’t scale. Because the assistant started taking over tons of of circumstances a day, we outgrew the dimensions at which our “breadcrumbs” methodology was efficient, and it was not possible for us to handle as people.
Figuring out the place, when, and why one thing went fallacious had turn out to be a time-consuming problem for the groups working the assistant. We shortly realized we would have liked to:
- Implement a brand new methodology that would scale with our operations
- Discover a resolution that would offer traceability and guarantee compliance
Scaling the AI Assistant for Help with Splunk
We determined to construct out a logging methodology utilizing Splunk, the place we may drop log messages into the platform and construct a dashboard with case quantity as an index. As an alternative of manually sifting by our “breadcrumbs,” we may instantaneously find the circumstances and workflows we would have liked to hint the actions taken by the assistant. The troubleshooting that will have taken us hours with our unique methodology might be achieved in seconds with Splunk.
The Splunk platform provides a sturdy and scalable resolution for monitoring and logging that allows the capabilities required for extra environment friendly knowledge administration and troubleshooting. Its skill to ingest giant volumes of knowledge at excessive charges was essential for our operations. As an trade chief in case search indexing and knowledge ingestion, Splunk may simply handle the elevated knowledge stream and operational calls for that our earlier methodology couldn’t.
Tangible advantages of Splunk
Splunk unlocked a degree of resiliency for our AI Assistant for Help that positively impacted our engineers, clients, and enterprise.
Fig. 2: The Splunk dashboard provides clear visibility into features to make sure optimized efficiency and stability.
With Splunk, we now have:
- Scalability and effectivity: Splunk displays the assistant’s actions to make sure it’s working accurately and supplies the power for TAC engineers to observe and troubleshoot workflows, permitting the assistant to effectively scale. The AI Assistant for Help has efficiently labored on over a million circumstances to this point.
- Enhanced visibility: With dashboards that permit for fast entry to case histories and workflow logs of our assistant, the TAC engineers overseeing the processes save time on case evaluations to ship quicker than ever buyer help.
- Optimized processes with real-time metrics: The visibility into useful resource allocation permits us to optimize our enterprise processes and workflows, in addition to reveal the worth of our resolution with real-time metrics.
- Proactive monitoring: Splunk ensures all APIs are absolutely functioning and displays logs to alert us of potential points that would impression our AI Assistant’s skill to function, permitting for fast remediation earlier than buyer expertise is impacted.
- Greater worker and buyer satisfaction: Engineers are geared up to deal with greater caseloads and effectively reprioritize efforts, decreasing burnout whereas optimizing buyer expertise.
- Lowered complexity: The dashboards have a easy interface, making it a lot simpler to coach and onboard new workers. The convenience of use additionally serves to enhance the capabilities of the people working our AI Assistant by enhancing their accuracy and effectivity.
By offering a scalable and traceable resolution that helps us keep compliant, Splunk has enabled us to take care of our dedication to distinctive customer support by our AI Assistant for Help.
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