Cisco wanted to scale its digital assist engineer that assists its technical assist groups around the globe. By leveraging its personal Splunk know-how, Cisco was in a position to scale the AI assistant to assist greater than 1M circumstances and release engineers to focus on extra advanced circumstances, making a 93+% buyer satisfaction score, and guaranteeing the crucial assist continues operating within the face of any disruption.
If you happen to’ve ever opened a assist case with Cisco, it’s doubtless that the Technical Help Heart (TAC) got here to your rescue. This around-the-clock, award-winning technical assist workforce providers on-line and over-the-phone assist to all of Cisco’s clients, companions, and distributors. In truth, it handles 1.5 million circumstances around the globe yearly.
Fast, correct, and constant assist is crucial to guaranteeing the shopper satisfaction that helps us keep our excessive requirements and develop our enterprise. Nonetheless, major occasions like crucial vulnerabilities or outages can trigger spikes within the quantity of circumstances that slow response occasions and rapidly swamp our TAC groups, impressioning buyer satisfaction consequently. we’ll dive into the AI-powered assist assistant that assists to ease this concern, 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 Assist
workforce of elite TAC engineers with a ardour for innovation set out to construct an answer that might speed up concern decision occasions by increaseing an engineers’ potential to detect and resolve 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 Assist or the human engineer based mostly on which is most acceptable for decision.
By immediately plugging into the case routing system to research each case that is available in, the AI Assistant for Assist evaluates which of them it may simply assist resolve, together with license transactions and procedural issues, and responds on to clients of their most popular language.
With such nice success, we set our eyes on much more assist for our engineers and clients. Whereas the AI Assistant for Assist was initially conceived to assist with the high-volume occasions that create a big inflow of circumstances, it rapidly expanded to incorporate extra day-to-day buyer points, serving to to cut back response occasions and imply time to decision whereas persistently sustaining a 93+% buyer satisfaction rating.
Nonetheless, as the usage of the AI Assistant grew, so did the complexity and quantity of circumstances it dealt with. An answer that after dealt with 10-12 circumstances a day rapidly ballooned into tons of, outgrowing the methodology initially in place for monitoring workflows and sifting by means of log information.
Initially, we created a technique often known as “breadcrumbs” that we tracked by means of a WebEx area. These “breadcrumbs,” or actions taken by the AI Assistant for Assist throughout a case from finish to finish, had been dropped into the area so we might manually return by means of 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 incorrect had turn into a time-consuming problem for the groups working the assistant. We rapidly realized we would have liked to:
- Implement a brand new methodology that might scale with our operations
- Discover a answer that would supply traceability and guarantee compliance
Scaling the AI Assistant for Assist with Splunk
We determined to construct out a logging methodology utilizing Splunk, the place we might drop log messages into the platform and construct a dashboard with case quantity as an index. As an alternative of manually sifting by means of our “breadcrumbs,” we might 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 completed in seconds with Splunk.
The Splunk platform provides a strong and scalable answer for monitoring and logging that permits the capabilities required for extra environment friendly information administration and troubleshooting. Its potential to ingest giant volumes of knowledge at excessive charges was essential for our operations. As an business chief in case search indexing and information ingestion, Splunk might simply handle the elevated information move 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 Assist that positively impacted our engineers, clients, and enterprise.
Fig. 2: The Splunk dashboard provides clear visibility into capabilities to make sure optimized efficiency and stability.
With Splunk, we now have:
- Scalability and effectivity: Splunk screens the assistant’s actions to make sure it’s working accurately and offers the power for TAC engineers to watch and troubleshoot workflows, permitting the assistant to effectively scale. The AI Assistant for Assist 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 opinions to ship quicker than ever buyer assist.
- Optimized processes with real-time metrics: The visibility into useful resource allocation permits us to optimize our enterprise processes and workflows, in addition to exhibit the worth of our answer with real-time metrics.
- Proactive monitoring: Splunk ensures all APIs are absolutely functioning and screens logs to alert us of potential points that might impression our AI Assistant’s potential to function, permitting for fast remediation earlier than buyer expertise is impacted.
- Larger worker and buyer satisfaction: Engineers are outfitted to deal with larger caseloads and effectively reprioritize efforts, lowering burnout whereas optimizing buyer expertise.
- Lowered complexity: The dashboards have a easy interface, making it a lot simpler to coach and onboard new staff. The benefit 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 answer that helps us keep compliant, Splunk has enabled us to keep up our dedication to distinctive customer support by means of our AI Assistant for Assist.
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