Seek lands $7.5M investment for AI that answers domain-specific questions • TechCrunch

Seek, a data analytics task automation platform, today announced it has raised $7.5 million in pre-seed and seed rounds with participation from Conviction Partners, Battery Ventures, and former Snowflake CEO Bob Muglia. CEO Sarah Nagy said the funding will be used to grow her Seek team over the next year, specifically in engineering and data science.

“I founded Seek last year after working as a quant and data scientist for over a decade,” Nagy said in an email interview with TechCrunch. “I wanted to solve a problem that I have encountered many times throughout my career. It often happens. For example, a sales rep sent me a message asking me to pull some basic and custom statistics for their customers. Adds long-term value to the business, I would be frustrated because it takes time away from the research I wanted to do. was also really annoying. ”

Seek’s core product is a natural language interface for data that plugs into existing data and communication tools, including cloud data warehouses within the business (that is, analytical databases stored in the public cloud). Users can ask her Seek questions that they would normally ask the data team in apps like Slack, Microsoft Teams, and email.

Powering Seek’s search and cataloging capabilities is a family of AI language models trained on data including e-books, online articles, websites, and proprietary data. The platform stores both questions and answers from users within its knowledge base so you can find them quickly. This way, Nagy says, Seek will be able to process more “intelligently” with the company’s data.

“Seek is looking to data teams to automate mundane manual tasks that had to be done manually because they were previously too complex to automate,” says Nagy. “As a former data scientist doing this type of work, my quality of life would be improved if these tasks were automated, and the work that could have been done in the time saved would pay off in the long run. I know there was a fundamental difference between my company’s strategy and our product.”

Recent news about AI often presents answers with confidence only to be found to be biased or untruthful. When asked about what Seek is doing about his AI at the company, Nagy said he was applying for a “control flow” patent to limit the inaccuracies presented to users. I was.

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“As the hype cycle of generative AI unfolds, we anticipate more conversations about flaws in the quality of AI-generated content and how users can protect themselves from inaccuracies.” he added. “We hope to be the thought leader when it comes to educating our customers on how to maximize the benefits of generative AI while having the right processes in place to address its limitations.”

Seek falls into the category of enterprise search engines known as “cognitive search.” Competitors include Amazon Kendra and Microsoft SharePoint Syntex. They utilize a knowledge base to compile answers to company-specific questions. Startups such as Hebbia, Kagi, Andi, and also leverage AI models to respond to queries and return specific content, rather than a simple list of results.

Despite the competition, Seek, which has nine employees, was able to sign “household name” customers, Nagy claims. He declined to disclose earnings or names, but Seek’s about a dozen clients (ranging from “startups to Fortune 100”) come from industries such as his B2B software as a service, fintech and direct to consumer sales. I said yes. and consumer packaged goods.

“Generative AI seems to be an exception to the current technology slowdown. Seek has benefited from the explosive popularity of tools like ChatGPT,” said Muglia. “[Moreover,] Seek was founded after the pandemic and its users are knowledge workers who can work from home. My hypothesis for building Seek has strengthened as corporate digital transformation initiatives accelerated during the pandemic, with more organizations adopting ambitious data initiatives. ”

According to Nagy, in the coming months Seek will focus on: Building app integrations, making the onboarding process more automated, and “continuously improving our customers’ experience on our platform.”

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