Cisco wanted to scale its digital assist engineer that assists its technical assist groups world wide. By leveraging its personal Splunk know-how, Cisco was in a position to scale the AI assistant to assist greater than 1M instances and unlock engineers to focus on extra advanced instances, making a 93+% buyer satisfaction score, and guaranteeing the vital assist continues working within the face of any disruption.
In case you’ve ever opened a assist case with Cisco, it’s seemingly that the Technical Help Heart (TAC) got here to your rescue. This around-the-clock, award-winning technical assist staff providers on-line and over-the-phone assist to all of Cisco’s clients, companions, and distributors. In truth, it handles 1.5 million instances world wide yearly.
Fast, correct, and constant assist is vital to guaranteeing the shopper satisfaction that helps us preserve our excessive requirements and develop our enterprise. Nonetheless, major occasions like vital vulnerabilities or outages can trigger spikes within the quantity of instances 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 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
staff of elite TAC engineers with a ardour for innovation set out to construct an answer that might speed up concern decision instances by increaseing an engineers’ capacity to detect and clear up 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 instances are analyzed and directed to the AI Assistant for Assist or the human engineer based mostly on which is most acceptable for decision.
By straight plugging into the case routing system to research each case that is available in, the AI Assistant for Assist evaluates which of them it will probably simply assist clear up, 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 Assist was initially conceived to assist with the high-volume occasions that create a big inflow of instances, it rapidly expanded to incorporate extra day-to-day buyer points, serving to to cut back response instances 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 instances it dealt with. An answer that after dealt with 10-12 instances a day rapidly ballooned into lots of, outgrowing the methodology initially in place for monitoring workflows and sifting by means of log information.
Initially, we created a technique generally known as “breadcrumbs” that we tracked by means of a WebEx house. These “breadcrumbs,” or actions taken by the AI Assistant for Assist 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 instances a day, this was all we wanted.
The issue was it couldn’t scale. Because the assistant started taking up lots of of instances a day, we outgrew the size at which our “breadcrumbs” technique was efficient, and it was not possible for us to handle as people.
Figuring out the place, when, and why one thing went flawed had turn out to be a time-consuming problem for the groups working the assistant. We rapidly realized we wanted to:
- Implement a brand new methodology that might scale with our operations
- Discover a answer that would offer 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 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 instances and workflows we wanted to hint the actions taken by the assistant. The troubleshooting that might have taken us hours with our unique methodology could possibly be achieved in seconds with Splunk.
The Splunk platform presents a strong and scalable answer for monitoring and logging that allows the capabilities required for extra environment friendly information administration and troubleshooting. Its capacity to ingest giant volumes of knowledge at excessive charges was essential for our operations. As an trade chief in case search indexing and information ingestion, Splunk may simply handle the elevated information circulation and operational calls for that our earlier methodology couldn’t.
Tangible advantages of Splunk
Splunk unlocked a stage of resiliency for our AI Assistant for Assist that positively impacted our engineers, clients, and enterprise.
Fig. 2: The Splunk dashboard presents 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 appropriately and supplies the flexibility 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 instances 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 critiques 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 totally functioning and displays logs to alert us of potential points that might impression our AI Assistant’s capacity to function, permitting for fast remediation earlier than buyer expertise is impacted.
- Increased worker and buyer satisfaction: Engineers are geared up to deal with greater caseloads and effectively reprioritize efforts, decreasing burnout whereas optimizing buyer expertise.
- Diminished 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 take care of our dedication to distinctive customer support by means of our AI Assistant for Assist.
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