In the mean time, large organizations often employ “business intelligence” (BI) tools to determine what the heck is occurring inside their operations. This has spawned many lumbering leviathans within the software world.
Now, UK startup Fluent has closed a $7.5 million seed investment round led by Hoxton Ventures and Tiferes Ventures to use AI-based Large Language Models (LLMs) to business databases, making them far easier to interrogate by the typical person.
Essentially, BI tools hook up with a business database and use SQL to create visualizations and construct out BI dashboards. There are huge corporations involved on this space: Tableau (owned by Salesforce), Power BI (owned by Microsoft), Looker (owned by Google), and QuickSight (owned by Amazon) to call only a handful.
The marketplace for solutions is very large. In accordance with one report, the worldwide business intelligence market was valued at $27.11 billion in 2022 and is projected to grow from $29.42 billion in 2023 to $54.27 billion by 2030. Gartner thinks it might be even larger if AI and LLMs are more widely applied.
Nevertheless, data teams spend numerous time constructing out these dashboards, especially for big organizations. And there may be at all times the challenge getting people to really use them — a tough task when data teams groan on the considered fulfilling requests that might take days to construct.
As an alternative, Fluent desires to be a “conversational layer” via natural-language LLMs that sit on top of an organization’s data warehouse. It translates those questions into SQL and generates those answers much faster. So anyone, no matter technical skills or business context, can ask questions in plain English of their data and procure insights, in accordance with the corporate.
After all, that is more likely to significantly shorten response times. Robert Van Den Bergh, CEO of Fluent, told me: “Consultants move from waiting 2 weeks for an insight to 30 seconds. Which means they ask lots more questions, use data considerably more of their job. Data becomes something that’s now of their reach.”
Fluent’s clients already include Bain & Company.
Although he admits Fluent is “primarily using Azure OpenAI’s GPT4 model,” he stressed this shouldn’t be a startup with an “OpenAI wrapper.”
That simplistic approach doesn’t work for generating accurate SQL and, subsequently, correct answers to data questions within the BI tools context, he claimed. “Through 18 months of labor, we’ve been capable of construct a technique to realize the accuracy of answers that organisations like Bain & Company can trust and leverage across their organisations.”
Ian Weber, a partner at Bain & Company, said in a supporting statement, “Fluent’s platform has helped us leverage LLMs to interrogate and deliver insights from large complex datasets. Fluent allows our consultants to quickly get the answers they need efficiently and accurately, especially for questions too complex or specific for pre-built data dashboards.”
Van Den Bergh said, “All business users want is answers to questions. They don’t need to do modelling. They need to understand how this client was performing versus this client. Or how [they are] doing here. And the way is that this marketing campaign performing.” He said other players out there goal data users, whereas Fluent targets the business market, not data.
The space of natural language querying has only recently develop into possible, so it’s not yet a crowded market.
For instance, Metabase is an open-source analytics and business intelligence application that permits users to create dashboards more easily. The SF-based company has raised $51 million so far.
Einblick, is a U.S. company that was recently acquired by Databricks (which is positioning to go public), appears to be the closest player to Fluent out there. Nevertheless, Fluent claims Einblick’s offering tends towards more technical users inside data teams.
Thoughtspot, which has claimed a $4 billion valuation, now also has a natural language querying system.