Hasselt, Belgium-based DataOps software maker, Timeseer has raised $6 million in a seed funding round. Looking at our AI-driven future, Timeseer is aiming to trim the fat on the stumbling block du jour, unreliable data. The funding is expected to be used to further develop the platform, drive a push into the North American market, and continue to position the company as a market leader in the time-series data reliability space.
For better or for worse, for richer and for poorer, whether we like it or not, the future is AI. And it will probably be televised. But just like the development of any complex machine, incremental steps must be made. To put things into perspective, if you think about a car as the end goal, we’re still putting the final touches on inventing the wheel.
One key factor holding AI back is bad data, or rather, I should say, unreliable data. As the AI-arms race presses forward, and every company and their cousin is looking into how they can carve out a competitive advantage by leveraging massive pools of data, this also puts them at risk. The phrase, “time is money,” is perhaps most appropriate here, as any downtime in the development process, i.e. bad or erroneous data, can have significant negative impacts on downstream analytics. What’s worse, these errors often go undetected. That is, until these negative impacts manifest themselves.
To put some numbers to paper, according to Timeseer, when looking solely at data captured by IoT devices, approximately 20% of it is unreliable. Now when you follow this negative impact all the way over to the finance department, that figure translates into around 6% of total revenue.
And it's not just the data teams that are struggling, these headaches run all the way up the ladder. According to a survey conducted by KPMG back in 2017, i.e. prior to the pandemic, prior to a massive shift in consumer behaviours, of the 1,300 CEO queried, more than half reported concerns over the integrity of the data they are using for decision-making, and slightly less than half indicating that the depth of their customer insight is hindered by a lack of quality customer data.
And herein lies the fundamental problem that Timeseer is aiming to solve. Or at least bring that 20% figure down significantly. By providing an AI-powered (yes, the machines are now training the machines) time-series data observation mechanism, the company argues that data teams now have access to, and confidence in, vastly more accurate data pools to draw from.
“Timeseer.AI will be focusing on time-series data because this is an underserved segment, and the temporal aspect of time-series and its metadata calls for a specific approach. The Timeseer.AI founding team alone has 80+ person-years of experience in the time-series domain, so this gives us the perfect starting position,” explained Timeseer’s chief product and strategy officer Thomas Dhollander.
Founded in late March of 2020, despite operating in stealth mode, the Belgian startup has already attracted the attention of a number of clients across a variety of verticals, and noted that they're working with, “more than a dozen Fortune 5000 companies.”
Timeseer’s $6 million seed funding round was led by Crane Venture Partners, with Smartfin Capital acting as a cornerstone investor. The round also saw participation from Fortino Capital, LRM, and Innovation Fund.
“We loved everything about the founding team: their early product and their ultimate vision from the very first meeting. They are obsessed with driving massive outcomes for their customers, which they have already proven with some of the largest and most demanding data-driven enterprises in the world,” commented Crane Venture Partners’ co-founder Scott Sage. “The time series data operations market is just getting going, and Timeseer.AI is poised to be a major player.”
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