How Tellius Kaiya Makes Data Interaction a Two-Way Street

kaiya-in-tellius-5.2

Remember when Google revolutionized how we navigate the internet, shifting us from endless scrolling to quick searching? Today, AI models like ChatGPT are taking it a step further, turning our interactions into dynamic conversations rather than one-way commands. Yet, despite this conversational revolution touching nearly every aspect of our lives, the data and analytics world remains stubbornly stuck in the past—rigid dashboards, static reports, and a frustratingly slow cycle of requests and delays.

Why is it that in an age where we can chat with our devices, order products with a voice command, and get instant answers from AI, interacting with enterprise data feels like talking to a one-dimensional character?

data analyst brick wall

Meet Mike, a marketing manager at a leading consumer packaged goods (CPG) company. Every day, Mike grapples with the same challenge: turning vast amounts of data into actionable insights before the next big meeting. He’s not a data analyst, but his role demands quick access to accurate information. The struggle? Traditional data platforms feel like a one-way street—rigid and unresponsive, and often more of a hindrance than help.

Enter Tellius Kaiya, with its all-new conversational AI interface. Kaiya transforms data interaction into a two-way dialogue, allowing business users like Mike to teach, adapt, and steer the conversation in real time.

In this blog, we’ll dive deep into Mike’s journey from frustration to empowerment, highlighting how Kaiya addresses common struggles faced by business users in the CPG, pharma, high-tech, and other various industries.

Ramya Priya

Written by: Ramya Priya,

Product Content and Strategy Lead at Tellius

Mike's daily struggles

Every morning, Mike braces himself for the inevitable data deep dive. He’s got a meeting in two hours, and he needs to present regional sales insights for the past quarter. But the obstacles are plenty:

  • Dependency on analysts: Without a data analyst’s help, navigating complex databases gets difficult.
  • Selecting the right dataset: Mike often second-guesses whether he’s looking at the correct dataset, leading to inconsistent reports.
  • Structuring queries correctly: Crafting the perfect query is time-consuming—one wrong word, and the entire results change.
  • Rigid platforms: Traditional tools don’t adapt to Mike’s needs; if the platform misunderstands, it’s back to square one, trying to find workarounds.
  • No feedback mechanism: There’s no way to correct the platform or teach it his preferences—it’s a one-way street.
  • Tweaking is impossible: Making quick adjustments to charts on the go is not available, forcing him to start over.

data struggles

Mike tests Kaiya—overcoming the struggles

With a deep breath, Mike types:

“Show me the quarterly sales performance of our top 5 products in the Northeast region and compare it to last year’s figures.”

Kaiya instantly processes the question, selects the appropriate Business View, and before displaying the chart, provides a concise summary:

“Your top 5 products in the Northeast region have seen an overall sales increase of 8% compared to last year, with ‘EcoPure v3’ leading at a 12% growth.”

In addition to displaying the results, Kaiya narrates the story behind the numbers. This quick insight gives Mike a clear overview without sifting through the data. But he notices that one product seems off—it’s showing data for a similar product line but not the exact one he’s interested in.

Mike clicks the Thumbs Down button and prompts that he meant “EcoFresh” and not “EcoPure” line of products.

Kaiya adjusts immediately, updating the chart with the correct product data.

But it doesn’t stop there. Kaiya records Mike’s feedback and remembers his preference for future queries. By saving this interaction as a Learning, Mike ensures that Kaiya instantly applies this preference for similar queries. His corrections aren’t just a one-time fix—they’re saved for eternity, making future interactions even smoother.

Noticing the dip in sales for Q2, Kaiya proactively suggests a follow-up:

“Would you like to see the factors contributing to the decline in Q2 sales for ‘EcoFresh’?” “Absolutely,” Mike replies.

Kaiya dives deeper, providing a contextual summary that includes market trends, regional performance, and competitor activities.

Mike wants to present this data differently. Instead of rephrasing the previous questions, he simply clicks on the chart and switches it from a bar graph to a tree map. No need to tweak questions or start over—the chart updates instantly, keeping his momentum going.

“It’s like having a conversation with my data,” Mike muses. “Finally, a two-way street.”

Turning data interaction into a two-way conversation

Thanks to the all-new conversational Kaiya, Mike navigates the data himself, reducing dependency on others. What used to take hours and multiple emails to analysts now takes minutes. Here are the key features that have transformed Mike’s workflow:

  • Conversational interface: Mike can now ask questions as he thinks of them, without worrying about formal query structure.
  • Feedback loop with thumbs up/down: If Kaiya’s response isn’t quite right, Mike can give immediate feedback, teaching Kaiya to improve future interactions.
  • Adaptive learning: Kaiya doesn’t just take feedback—it learns from it, adapting to Mike’s way of asking questions and preferences.
  • SmartSelect: Kaiya auto-selects the most relevant Business View, eliminating Mike’s uncertainty about datasets.
  • Saving Learnings: Mike can save specific interactions as “Learnings,” allowing Kaiya to recall his preferences and frequently asked queries.

The more you use Kaiya, the better it gets

A month into using Kaiya, Mike notices a remarkable transformation in his workflow. Each interaction refines Kaiya’s understanding of his needs. The more feedback Mike provides, the more adaptive Kaiya becomes. It starts to apply his preferences automatically, delivering answers more accurately. Kaiya doesn’t just learn—it evolves with Mike, becoming more personalized with each use.

  • Empowerment: He’s no longer at the mercy of complex platforms or waiting on analysts.
  • Adaptability: The more he uses Kaiya, the more it learns and adapts to his style, providing faster, more accurate answers.
  • Personalization: Kaiya automatically applies the preferences, so Mike doesn’t have to reinvent the wheel each time.
  • Efficiency: Immediate feedback mechanisms mean he can course-correct on the fly, saving time in the long run.
  • Deepened understanding: Kaiya becomes accustomed to Mike’s workflow, making the interaction seamless and intuitive.

Expanding horizons—Kaiya across industries

Emily, a business development manager at a pharmaceutical company, faces similar hurdles. She’s tasked with tracking prescription trends but often gets bogged down:

  • Double-checking data sources with analysts.
  • Struggling with complex query structures.
  • Dealing with static platforms that don’t adapt to her needs.

With Kaiya, Emily asks:

“Compare monthly prescription rates for ‘MedX’ in the top 15 hospitals and highlight any significant changes.”

When the initial data seems off, she gives a Thumbs Down and corrects to focus only on hospitals in the Midwest region.

Kaiya adapts instantly, updating the data, and providing a summary along with the results:

“In the past month, ‘MedX’ prescriptions increased by 12% in the Midwest region, particularly in Central Medical Center.”

Moreover, Emily saves this preference, so future queries automatically focus on the Midwest unless specified otherwise.

Emily wants to present this data differently. She quickly asks Kaiya “Use scatter plot chart instead of line chart” and Kaiya delivers the updated chart, without wasting time. The more Emily interacts with Kaiya, the more it aligns with her analytical needs, providing faster and more accurate insights.

Are you ready to turn your data journey into a two-way conversation?

Mike’s and Emily’s journeys mirror the experiences of countless business users who have felt constrained by traditional data tools. Kaiya represents a shift towards platforms that not only provide answers but also learn and adapt from each interaction.

With Kaiya in Tellius 5.2, the days of one-sided data struggles are over. Corrections and preferences aren’t lost; they’re saved and leveraged in your future interactions. It’s a tool that grows with you—the more you interact with Kaiya, the more it becomes accustomed to your preferences, delivering faster and more accurate answers.

Start the dialogue today and discover how personalized insights are just a conversation away.

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