Fluent, a platform specializing in data analytics that transforms the way decision-makers access and use business data, recently concluded a seed investment round of approximately £6 million. The platform, powered by AI, grants non-technical team members the ability to ask questions directly from their data in plain English, allowing them to get insights in seconds that save data teams from manually replying to ad hoc data requests. The investment round was led by Hoxton Ventures and Tiferes Ventures, and the funds will be used to expedite the development of Fluent’s revolutionary technology, as well as expand its team of AI and machine learning professionals in Europe.
“On average, 40% of a data team’s time is spent answering questions from across their business,” said Fluent CEO, Robert Van Den Bergh. “A lot of these questions are easy to answer for the data team but take them away from the deeper, more strategic analysis that can be transformative to their business. With Fluent’s natural language interface, we’re helping team members self-serve on their data questions.”
Fluent has impressively accumulated influential clients, with Bain & Company being one of them. The platform has enabled them to leverage LLMs to interrogate and deliver insights from large complex datasets. “Fluent allows our non-technical users to quickly get the answers they need efficiently and accurately, especially for questions too complex or specific for pre-built data dashboards. We’re excited to explore how Fluent can help our clients better access data and insights in the future,” said Ian Weber, a Partner at Bain & Company.
Charles Seely, Partner at Hoxton Ventures, also shared his thoughts on Fluent, stating that in a data-driven world, the current approach to data analysis is insufficient, creating permanent bottlenecks in organizations that not only slow everyone down but also hamper decision-making. “Fluent’s approach is not just innovative, it’s urgently needed, and we’re excited to be part of their journey in reshaping how businesses interact with data,” he added.
