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Advanced AI News
Customer Service AI

TS Imagine develops customer service bot atop Snowflake

By Advanced AI EditorJune 5, 2025No Comments4 Mins Read
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Generative artificial intelligence has become the new vanguard of customer service for companies handling sensitive data, especially in the financial sector.

TS Imagine Inc., which offers a software-as-a-service platform for trading and risk management, has undergone remarkable transformation using Snowflake Inc.’s Data Cloud platform. Once Snowflake integrated AI into its platform, TS Imagine embraced chatbots and agents as the next stage of customer service and analysis.

Vivek Raghunathan, senior VP of engineering at Snowflake, and Thomas Bodenski, COO and chief data and analytics officer at TS Imagine, discuss Taya, TS Imagine's customer service chatbot on the set of theCUBE.

The set of theCUBE at Snowflake Summit 2025.

“We chose Snowflake almost four years ago to be our data access layer because of its data sharing capabilities,” said Thomas Bodenski (pictured, right), chief operating officer and chief data and analytics officer at TS Imagine. “AI didn’t exist back then, ChatGPT wasn’t born back then, and that was our vision to have that. Now, fast forward you have the AI running natively on the same data. So, we bring the AI to the data rather than the data to the AI.”

Bodenski and Vivek Raghunathan (pictured, left), senior vice president of engineering at Snowflake, spoke with theCUBE’s Rebecca Knight and Dave Vellante at Snowflake Summit, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed how Snowflake has changed the way TS Imagine handles data. (* Disclosure below.)

Developing a unique customer service bot

Snowflake’s goal is preparing its clients’ data for increasingly complex tasks, such as semantic analysis, while keeping it secure and governed with the Snowflake platform. Its accessible tools enable data analysts to be AI engineers, according to Bodenski and Raghunathan.

“The vision we are powering towards very much is AI gets integrated in the database in a way that was never before,” Raghunathan said. “You can analyze … multimodal content alongside all your other analytical content using LLMs almost as a prompt. You can imagine how this might transform industries where people are dealing with lots of multimodal and analytic data at the same time.”

TS Imagine is in one such industry. After Snowflake integrated AI into its platform, TS Imagine was able to enhance its business operations by developing their own chatbot, branded as “Taia.” The chatbot functions as a customer support agent, analyst and even salesperson, according to Bodenski.

“She’s part of the team, works 24-7 and produces amazing results,” he said. “One of the really exciting use cases that we have up and running is actually for our customer service inquiry. We have 60,000 customer service inquiries a year, 5,000 approximately a month. Because we are in trading and risk management, those inquiries are not easy to remediate or to work on.”

Taia was built by data scientists and analysts who had limited or no background in AI. It’s able to handle the thousands of inquiries efficiently, enabling employees to focus on higher-level decision-making. Raghunathan predicts that getting a return on investment for chatbots and agents such as Taia will only get easier in the coming year.

“Every six months, the length of tasks that an AI can do by itself is roughly doubling,” he said. “That means the time to value is reducing, is shrinking. The time to be able to do these tasks with high ROI is increasing.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of Snowflake Summit:

(* Disclosure: TheCUBE is a paid media partner for Snowflake Summit. Neither Snowflake Inc., the primary sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE

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