Cisco wanted to scale its digital assist engineer that assists its technical assist groups all over the world. By leveraging its personal Splunk expertise, Cisco was capable of scale the AI assistant to assist greater than 1M instances and unencumber engineers to focus on extra complicated instances, making a 93+% buyer satisfaction ranking, and making certain 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 Middle (TAC) got here to your rescue. This around-the-clock, award-winning technical assist staff companies on-line and over-the-phone assist to all of Cisco’s prospects, companions, and distributors. In truth, it handles 1.5 million instances all over the world yearly.
Fast, correct, and constant assist is crucial to making certain the shopper satisfaction that helps us preserve our excessive requirements and develop our enterprise. Nonetheless, major occasions like crucial vulnerabilities or outages can trigger spikes within the quantity of instances that slow response occasions and shortly swamp our TAC groups, influenceing 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 expertise 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 would speed up problem decision occasions by increaseing an engineers’ means 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 instances are analyzed and directed to the AI Assistant for Assist or the human engineer primarily based on which is most applicable for decision.
By immediately plugging into the case routing system to investigate each case that is available in, the AI Assistant for Assist evaluates which of them it might probably simply assist resolve, together with license transactions and procedural issues, and responds on to prospects of their most popular language.
With such nice success, we set our eyes on much more assist for our engineers and prospects. Whereas the AI Assistant for Assist was initially conceived to assist with the high-volume occasions that create a big inflow of instances, it shortly expanded to incorporate extra day-to-day buyer points, serving to to cut back response occasions and imply time to decision whereas constantly 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 shortly ballooned into lots of, outgrowing the methodology initially in place for monitoring workflows and sifting by means of log information.
Initially, we created a strategy often 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 might 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 would have liked.
The issue was it couldn’t scale. Because the assistant started taking up lots of of instances a day, we outgrew the dimensions 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 improper 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 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 instances 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 might be completed in seconds with Splunk.
The Splunk platform gives a sturdy and scalable resolution for monitoring and logging that permits the capabilities required for extra environment friendly information administration and troubleshooting. Its means 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 might simply handle the elevated information circulate 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, prospects, and enterprise.
Fig. 2: The Splunk dashboard gives 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 gives 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 so far.
- 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 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 resolution with real-time metrics.
- Proactive monitoring: Splunk ensures all APIs are totally functioning and displays logs to alert us of potential points that would influence our AI Assistant’s means to function, permitting for fast remediation earlier than buyer expertise is impacted.
- Greater worker and buyer satisfaction: Engineers are outfitted to deal with increased caseloads and effectively reprioritize efforts, lowering burnout whereas optimizing buyer expertise.
- Decreased 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 keep up our dedication to distinctive customer support by means of our AI Assistant for Assist.
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