Overview
Qumulo is a leading file data platform designed to simplify unstructured data management in the cloud and on-premises. Founded in 2012 and headquartered in Seattle, Washington, Qumulo provides scalable solutions for managing massive data stores that hold trillions of files.
These solutions are used daily by companies from many industries, such as media and entertainment, healthcare, financial services, life sciences, higher education, and the public sector. Qumulo’s proven platform offers real-time visibility, control, and seamless integration across edge, core, and cloud environments.
The company has been recognized for its innovative data management solutions and has a strong customer base that includes Fortune 500 companies and major research facilities.
Objective
The goal of this project was a revamp of the search functionality of Qumulo’s key web properties—the Documentation Portal, Qumulo Care, and the main qumulo.com website (which have different audiences and content)—by providing relevant, snippet-length summaries alongside AI-driven search results.
Previously, the Documentation Portal relied on keyword-based lookups that required keywords to be added to individual pages in advance; Qumulo Care and the main website used search solutions built into their respective CMS systems.
By integrating Vectara’s AI-driven advanced search capabilities into Qumulo’s web properties, Qumulo sought to create a system that would perform comprehensive searches on document bodies, provide a consistent search experience, and give users fast summaries to help them grasp the essence of technical documents, white papers—and more—at a glance.
Challenge
During the evaluation period, Qumulo considered alternatives such as Google Vertex AI Search, Azure AI Search, Elastic, and Algolia to determine key requirements. They realized that they wanted to avoid vendor lock-in, manage costs as they scaled, and customize the search solution to suit their different web properties.
Vectara’s flexibility was particularly beneficial, allowing Qumulo to make API calls while remaining largely agnostic of the underlying AI technologies. This flexibility is maintained even if Vectara switches or adds new AI engines.
Vectara also met Qumulo’s cost requirements with its pay-as-you-go model as part of its Scale plan.
Vectara engineers worked closely with Qumulo, providing code examples, addressing issues they raised on GitHub, and adjusting the product in response to Qumulo’s requirements during the adoption period.
Key outcomes
The integration of Vectara’s AI-driven search has significantly improved Qumulo’s search functionality. With Vectara, Google Analytics shows that their search page quickly became the second-most-accessed page on the Documentation Portal. Since the soft launch in February 2024, Qumulo has been tracking up to 170 daily search queries, with an average of 4 queries per user.
This enhancement, combined with existing navigational and structural element enhancements of docs.qumulo.com, has greatly increased the usability of the Documentation Portal. Implementing Vectara across their primary web properties has also facilitated tracking the most popular pages and the identification of content that might require updates or pruning.
This enhanced visibility allows Qumulo to make better decisions about integrated content management, ensuring that both prospective and current customers and Engineering and Customer Success staff at Qumulo have quick, consistent, and accurate access to information about their offerings on the market.
By up-leveling the search experience, Qumulo has enabled faster decision-making processes, boosted operational efficiency, and significantly enhanced user satisfaction across their customer-facing platform.
