Cisco wanted to scale its digital assist engineer that assists its technical assist groups all over the world. By leveraging its personal Splunk know-how, Cisco was capable of scale the AI assistant to assist greater than 1M circumstances and unencumber engineers to focus on extra complicated circumstances, making a 93+% buyer satisfaction ranking, and guaranteeing the essential assist continues operating within the face of any disruption.
In case you’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. Actually, it handles 1.5 million circumstances all over the world yearly.
Fast, correct, and constant assist is essential to guaranteeing the client satisfaction that helps us keep our excessive requirements and develop our enterprise. Nevertheless, major occasions like essential vulnerabilities or outages can trigger spikes within the quantity of circumstances that slow response instances and rapidly swamp our TAC groups, impressioning buyer satisfaction in consequence. we’ll dive into the AI-powered assist assistant that assists to ease this problem, in addition to how we used our personal Splunk know-how to scale its caseload and improve our digital resilience.
Constructing an AI Assistant for Help
workforce of elite TAC engineers with a ardour for innovation set out to construct an answer that would speed up problem decision instances by increaseing an engineers’ potential 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 acceptable 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 could 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 assist 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 rapidly expanded to incorporate extra day-to-day buyer points, serving to to cut back response instances and imply time to decision whereas constantly sustaining a 93+% buyer satisfaction rating.
Nevertheless, 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 lots of, outgrowing the methodology initially in place for monitoring workflows and sifting by means of log knowledge.
Initially, we created a technique referred to as “breadcrumbs” that we tracked by means of a WebEx house. These “breadcrumbs,” or actions taken by the AI Assistant for Help throughout a case from finish to finish, have been dropped into the house so we may 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 up lots of of circumstances a day, we outgrew the size 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 change 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 would scale with our operations
- Discover a answer 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 a substitute of manually sifting by means of 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 may have taken us hours with our authentic methodology could possibly be completed in seconds with Splunk.
The Splunk platform affords a strong and scalable answer for monitoring and logging that permits the capabilities required for extra environment friendly knowledge administration and troubleshooting. Its potential to ingest massive volumes of information at excessive charges was essential for our operations. As an business chief in case search indexing and knowledge ingestion, Splunk may simply handle the elevated knowledge circulation 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 affords 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 offers the power for TAC engineers to watch and troubleshoot workflows, permitting the assistant to effectively scale. The AI Assistant for Help has efficiently labored on over a million circumstances up to now.
- Enhanced visibility: With dashboards that enable 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 sooner 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 display the worth of our answer 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 potential to function, permitting for fast remediation earlier than buyer expertise is impacted.
- Greater worker and buyer satisfaction: Engineers are geared up to deal with larger caseloads and effectively reprioritize efforts, lowering burnout whereas optimizing buyer expertise.
- Diminished 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 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 Help.
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