Lisbon’s YData has secured €2.3 million in seed funding. The company joins the ranks of startups that use a data-centric approach in preparing data to be fed to help train AI products. The seed money will be used to help the startup accelerate its North American and European expansion plans. To date, YData has garnered approximately €2.8 million in funding.
Established in 2019, a full year after Balderton Capital-backed French competitor Kili Technology (who've banked $31.9 million), YData claims to be, “the first data preparation platform to accelerate the development of AI solutions".
YData uses data science frameworks and combines them with their own proprietary blend of tools for data access and profiling, data generation and labelling, with the output being high-quality data for AI models to ingest. Higher quality data results in fewer errors and, more/most importantly, unintentional bias, a problem we’ve seen time and time again.
“Typically, data scientists spend 80% of their time just cleaning and preparing data, whilst 85% of AI projects fail, mainly due to poor data quality,” explains co-founder and CEO Gonçalo Martins Ribeiro.
To support the next stage of the company’s growth, Riberio intends to move to the US, while the development team remains in Portugal. With this move, the US will see the bolstering of business development and product teams while Portugal and other European destinations will see the growth of tech development teams.
YData’s seed funding round was led by Flying Fish Partners and saw the participation of existing investors Faber, EDP Ventures, and Real Ventures.
“While at Microsoft, our key pain point when building AI systems was data. The team spent a huge amount of time, money, and data science resources on ensuring we had high-quality data and the right sets of data to build the models we needed,” comments Flying Fish’s Frank Chang. “The company built its own internal system to handle this, and I’m so excited to see YData tackling a very real problem that many companies will face, but don’t have the resources to solve internally.”
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