Cisco uses Elastic to save 5,000 support engineer hours a month

With the precision of search and the intelligence of AI, Cisco uses Elastic on Google Cloud to create richer search experiences, so support engineers can quickly find the answers they need. Scaling from this success, Cisco's Search team added AI models, semantic search, and vector search to more than 50 internal- and external-facing apps, helping them innovate more quickly and increase overall operational efficiency.

With more than two million service requests received each year, Cisco needed a solution that would help its 11,000 support engineers find answers by searching through its library of 50 million documents. Content search plays a key role in many areas of Cisco’s operations and is an essential feature on Cisco.com. With the need to provide employees, customers, and potential customers instant search to access the information they need, Cisco needed to ensure search experiences were accurate, efficient, and timely.

Using Elastic on Google Cloud, Cisco enables its support engineers to quickly retrieve documentation applicable to the customer service request. This means that when support engineers are on a call, they can find similar cases in real time using error messages related to the customer’s problem. From that, they will get relevant information from similar support cases, bug reports, knowledge articles, and internal discussion forums. This new search experience is able to solve 90% of service requests, freeing up support engineers' time to focus on more complex issues.

The Cisco.com search experience also went through a transformation. Using the same platform as the support engineer use case and Elastic's Search AI built on Google Cloud services, Cisco.com uses AI (neural question generation) to power autosuggestions. This solution has the capability for hybrid (semantic and textual) search on text passages. 

Among other benefits, Cisco saw an improvement in:

• User engagement: As a result of the new search capabilities, user engagement via click-through rates has gone up drastically, and the response time for a search query is now 73% faster, reducing the likelihood that people will lose interest while the page loads.

• Speed of innovation: Cisco has been able to innovate more quickly due to Elastic’s integration with the latest cloud technologies and platforms.

• Scalability: Elastic’s platform enables Cisco to continuously innovate by adding Search AI features, rolling out to more than 50 internal and external applications, with future potential for AIOps integration. 

• Elastic’s Search AI Platform makes data searchable and usable for artificial intelligence. With so much data and so many documents to analyze, Cisco needed a solution that could find the most relevant data and bring it to the forefront while learning as it went. 

• The resilience and scalability of Elasticsearch ensure a strong foundation with room to add more capabilities and use cases in the future. Cisco looks forward to opportunities to further streamline integration and AIOps.

• Elastic offers a 100% cloud-native solution that includes integration with Google Kubernetes Engine. This simplifies management and deployment while optimizing cost efficiency.

Contact us to learn how Elastic can help you save time and budget with Search AI.

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