ThoughtSpot integrates with GPT-3 to boost analytics suite

ThoughtSpot on Thursday launched the private preview of Sage, a new tool within the vendor’s platform that combines its existing search capabilities with GPT-3 and other large language models.

In addition, the analytics vendor unveiled an integration with GPT-3, which is a large language model (LLM) from OpenAI (also the creator of ChatGPT).

ThoughtSpot’s tools are designed to enable users to query and analyze data using natural language much the same way Google enables users to explore information by entering words into a search field.

Recently, the vendor, based in Mountain View, Calif., launched a series of partnerships and integrations aimed at expanding its capabilities.

Among them were a partnership with DBT Labs to augment ThoughtSpot’s self-service analytics capabilities, an integration with Google Sheets so that Sheets users can analyze their data with ThoughtSpot, and a partnership with Matillion to better enable joint users to ingest and integrate their data.

Now, following other tech vendors including Sisense, Salesforce and Microsoft that have also integrated with OpenAI’s LLMs, ThoughtSpot is adding an integration with GPT-3 to further broaden its capabilities. The company said it expects to make Sage generally available within the next three months.

Both Sage and its included integration with GPT-3 aim to strengthen the existing natural language search capabilities of the ThoughtSpot analytics suite with the natural language processing and generative AI powers of LLMs. But with Sage still in private preview, whether it actually improves upon ThoughtSpot’s existing natural language search remains to be seen, according to Doug Henschen, an analyst at Constellation Research. The proof will be in the performance and reliability of Sage and the analytic content and code it generates. “The proof will be in the performance and reliability of Sage and the analytic content and code it generates,” he said. “I’m seeing a lot of demos of new analytics capabilities built on generative AI lately, but they’re all in preview — if not private preview — at this point. We’ll have to wait and see how much time [Sage] saves and whether the content and code it generates is solid.” Assuming Sage delivers on its intent, it will make searching data more simple with ThoughtSpot while maintaining the accuracy of the vendor’s analytics platform. “ThoughtSpot says it’s a case of working ‘better together,’ with the company’s existing search experience enhanced and extended with generative AI,” Henschen said. That symbiosis is what’s key about Sage, according to Sumeet Arora, ThoughtSpot’s chief development officer. Despite ThoughtSpot’s focus on making data exploration as easy as possible through natural language search, the vendor’s platform still requires some level of data literacy, he noted. For example, the phrasing of business questions has to be precise to get the desired answer. When a question is asked of the platform, it uses AI developed by ThoughtSpot to convert data to what the vendor calls search tokens. Those tokens, however, are natural language-like as opposed to true natural language, Arora said. Therefore, users must formulate queries in ways the tokens are programmed to understand. Sage, however, through integrations with LLMs, infuses true natural language into the search tokens, thus eliminating data fluency as a prerequisite for ThoughtSpot’s use, Arora said. “That was the bridge to cross,” he said. The search tokens, meanwhile, remain necessary because they are the piece of ThoughtSpot’s platform that ensure accuracy. One of the drawbacks of LLMs so far is a lack of accuracy. In addition, ChatGPT — the best-known LLM to date — has access to data through only year’s end 2021.