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 in a position to scale the AI assistant to assist greater than 1M instances and liberate engineers to focus on extra complicated instances, making a 93+% buyer satisfaction score, and guaranteeing the essential assist continues operating within the face of any disruption.
Should you’ve ever opened a assist case with Cisco, it’s seemingly that the Technical Help Middle (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 instances all over the world yearly.
Fast, correct, and constant assist is essential to guaranteeing the client satisfaction that helps us preserve our excessive requirements and develop our enterprise. Nevertheless, major occasions like essential 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 situation, 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
workforce of elite TAC engineers with a ardour for innovation set out to construct an answer that might speed up situation 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 research each case that is available in, the AI Assistant for Assist evaluates which of them it could 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 major 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.
Nevertheless, as using the AI Assistant grew, so did the complexity and quantity of instances it dealt with. An answer that when dealt with 10-12 instances a day shortly ballooned into a whole bunch, outgrowing the methodology initially in place for monitoring workflows and sifting by log knowledge.
Initially, we created a strategy often called “breadcrumbs” that we tracked by a WebEx house. These “breadcrumbs,” or actions taken by the AI Assistant for Assist throughout a case from finish to finish, had been dropped into the house so we might manually return by 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 a whole bunch 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 mistaken had turn into a time-consuming problem for the groups working the assistant. We shortly 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 a substitute of manually sifting by 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 might have taken us hours with our authentic methodology may very well be completed in seconds with Splunk.
The Splunk platform provides a sturdy and scalable answer for monitoring and logging that permits the capabilities required for extra environment friendly knowledge administration and troubleshooting. Its means to ingest giant volumes of information at excessive charges was essential for our operations. As an trade chief in case search indexing and knowledge ingestion, Splunk might simply handle the elevated knowledge move 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 provides clear visibility into capabilities 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 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 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 show 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 might influence our AI Assistant’s means 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, decreasing 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 our AI Assistant for Assist.
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