Yellowfin boosts analytics suite with new NLQ capabilities

Catching up

Founded in 2003 in Melbourne, Australia, Yellowfin is a longtime analytics vendor that remained independent until it was acquired by Houston-based Idera, the parent company of dozens of B2B software vendors, in January 2022.

Yellowfin 9.17 is a significant release for Yellowfin users, but hardly radical in the industry. Indeed, it is really just a very basic catch-up on features that other vendors are already moving past. The NLQ features are important to keep Yellowfin relevant.

Before the acquisition, Yellowfin was renowned for its innovation and featured advanced embedded analytics, natural language processing and data storytelling capabilities. In addition, its mobile BI capabilities were respected.

However, as analytics has evolved over the past few years to include generative AI and agentic AI tools, Yellowfin has been slower than many of its peers to develop such capabilities, according to Farmer.

For example, ThoughtSpot in December unveiled plans to automate its entire analytics platform with agents. Similarly, Domo, Tableau and Qlik are among the analytics vendors now emphasizing agentic AI capabilities, including features such as Model Context Protocol (MCP) servers that help their many customers now interested in building and deploying agents of their own.

Yellowfin, though it includes AI features such as automated data blending and Signals to surface insights, has adapted more slowly and does not support MCP.

"Yellowfin had been well-loved for its innovation, usability and dedication to context-driven analytics prior to the acquisition," Farmer said. "Customers who bought Yellowfin for innovation have seen little to keep them interested."

Yellowfin's latest update, while it doesn't differentiate the vendor from peers, does feature capabilities that help it more closely compete, he continued.

The new NLQ capabilities, which build on those the vendor launched in April 2025, are more advanced than some competitor's NLQ tools. Yellowfin's NLQ interface behaves like a true chat, keeping previous queries, responses and context visible so that users can follow up on questions. Some competing vendor's NLQ tools do not retain context during an interaction and force users to restate context with each query.

In addition, the new user interface, performance improvements for large deployments and a single sign-on (SSO) option that improves security are all valuable, according to Farmer.

"Many Yellowfin users selected the original product for its ability to work at scale with hundreds of users, and there are some improvements noted here -- SSO sessions and improved performance -- which may enable Yellowfin to hold on to … enterprise customers," he said.

In particular, enterprises first attracted to Yellowfin by its performance and easy distribution of key analytics assets continue to benefit from the vendor's updates, Farmer added.

"Customers who bought primarily for those reasons have been happy enough," he said.

Leone likewise noted that the new features, highlighted by the NLQ capabilities, demonstrate that while Yellowfin might not yet be adding some of the more advanced tools some competitors now provide, it is adding features that cater to the needs of its existing customers.

"Yellowfin is clearly tracking where the broader market is heading, and they're making smart, deliberate choices about what to prioritize," he said. "Are the larger vendors further along on some of these capabilities? Sure. But Yellowfin has always played a different game, and for their embedded analytics audience, shipping a polished, well-integrated experience matters more than racing to be first."

However, whether the new capabilities can help Yellowfin restore the identity it had when it was an independent vendor and attract new customers in addition to appeasing existing ones remains to be seen, Leone continued.

"What I find encouraging is that the product hasn't stalled," he said. "They're still shipping meaningful releases, and this latest one shows they're paying attention to where analytics needs to go. The challenge now is making sure the market knows that, because the technology seems to be in a better place than the brand awareness might suggest."

While the new and improved capabilities help bring Yellowfin's platform more in line with those offered by competing analytics vendors, customer feedback provided the primary impetus for adding the features included in the vendor's latest update, according to Phoebe Xie, product director at Idera.

"Customer usage patterns and feedback were the primary drivers," she said. "We saw increasing demand for AI-assisted discovery and deeper BI insights. In response, we introduced context retention in NLQ so users can have continuous, meaningful conversations without losing their train of thought."

Next steps

As Yellowfin plots its product development initiatives over the coming months, some of the same themes addressed in its latest analytics platform update will be points of emphasis according to Xie.

For example, AI capabilities such as conversational querying and assisted storytelling are focal points. User experience improvements that better enable developers to embed Yellowfin in other work applications are also part of the vendor's roadmap, Xie said.

Although Yellowfin's AI features such as NLQ are useful and address the true needs of many analytics users, Leone advised the vendor to start adding agentic AI capabilities more in line with those of competitors.

"I'd love to see them explore agentic capabilities," he said. "The whole industry is moving toward analytics that can actually trigger actions and workflows, not just surface answers. Given Yellowfin's strength in embedded analytics, it's actually well-positioned for this because the idea of kicking off automated processes from inside someone else's application is a super compelling use case."

Farmer, meanwhile, suggested that Yellowfin add more proactive analytics capabilities and decision intelligence features.

"They have the basics in Signals, but they could do more in helping users anticipate opportunities or risks before they even ask a question and even potentially suggest additional analytics or possibly decisions," he said. "Signals was a cool feature in its day, and it deserves some love."

Eric Avidon is a senior news writer for Informa TechTarget and a journalist with more than three decades of experience. He covers analytics and data management.