Supersimple Raises $2.2 Million to Rethink How Companies Work With Data in Age of Artificial Intelligence

Pre-seed company and repeat AI founders target B2B SaaS companies with AI-native data analytics platform and empower anyone in the organization to answer complex ad-hoc data questions with no code

Supersimple, the AI-native data analytics platform that enables anyone to explore data and accurately answer complex questions in minutes, announced $2.2 million in pre-seed funding. The round is led by Tera Ventures with participation from Specialist VC, Tiny VC and a variety of angel investors that include the former CTO of Twilio and the founders of Sixfold and Grünfin.

With today’s Business Intelligence (BI) and data analytics tools being a combination of static dashboards and uninspired ChatGPT-esque chat interfaces, Supersimple is betting big on a future where enterprise software in the age of AI doesn’t look like chatbots and people are empowered with highly specific data insights, rather than a few high-level charts.

“What I love about Supersimple is that it lives up to its name. We’re trying to help our employees and customers make better decisions, not configure charts and queries,” said Tuomo Laine, CEO at Twice Commerce, a Supersimple customer. “Supersimple stands out by making it obvious how it came by the insights it’s sharing and making the user experience of double clicking on that as easy as ABC.”

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The funding will be used to accelerate customer growth and advance the state of the art in explainable AI. The Supersimple team includes software developers, data scientists and product designers with proven track records building deeply adopted technologies and successful startups. Co-founder and CTO Priit Haamer co-founded Sixfold where co-founder and CEO Marko Klopets also worked. The AI-based company merged with Transporeon and later sold for $2 billion. Most of Supersimple’s machine learning engineering team hails from Sixfold.

Supersimple’s AI-native data analytics platform combines a semantic data modeling layer and state-of-the-art explainable AI to give users reliable, consistent data to power their day-to-day work. Supersimple was designed specifically for teams at B2B SaaS companies to answer their own ad-hoc data questions, letting even non-technical team members go far beyond pre-built dashboards to get to data insights and make better decisions.

“Most of the value in data doesn’t come from staring at a dashboard. Instead, it comes from deep, specific questions – testing hypotheses, exploring and iterating. Supersimple was built around this insight to help teams always have the right information to make great decisions,” said Marko Klopets, co-founder and CEO at Supersimple. “Making structured data from data warehouses accessible and usable is the first step towards Supersimple becoming the operating system of the fastest growing companies.”

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Even though modern data stacks are better than ever before, organizations are still only scratching the surface of being able to get the right information to the right people. Thanks to recent advances in data warehouses and machine learning (including but not limited to large language models), it’s now possible to build entirely new user experiences to detect and explain valuable data insights, and to let users explore any follow-up questions. Supersimple believes that purpose-built, complete platforms are required to offer the level of versatility and trust that’s required among enterprises and for mission-critical workflows. The company is also putting an emphasis on user experience and design in a space that has traditionally made that a footnote.

The Supersimple data analytics platform gives everyone the ability to answer ad-hoc, complex data questions through its no-code and natural language interfaces without having to know or learn technologies like SQL or Python, or think in terms of database concepts. When asking questions in plain English, Supersimple’s AI explains every step it takes, eliminating hidden hallucinations, to make sure users can always trust its results. All this frees up the data team from fielding high volumes of data requests, allowing them to instead focus on company-wide strategic data initiatives and empowering the rest of their organization.

“Over the last few years, data warehouses have become ubiquitous and data stacks are better than ever. Yet companies are still struggling to actually make use of their data,” said Eamonn Carey, partner at Tera Ventures. “When I heard Marko explain his vision and I saw the platform in action, it became crystal clear that this is what the future would look like.”