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LatticeFlow raises $12M to eliminate computer vision blind spots

 2 years ago
source link: https://finance.yahoo.com/news/latticeflow-raises-12m-eliminate-computer-070158422.html
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LatticeFlow raises $12M to eliminate computer vision blind spots

Frederic Lardinois
Wed, October 26, 2022, 4:01 PM·4 min read

LatticeFlow, a startup that was spun out of Zurich's ETH in 2020, helps machine learning teams improve their AI vision models by automatically diagnosing issues and improving both the data and the models themselves. The company today announced that it has raised a $12 million Series A funding round led by Atlantic Bridge and OpenOcean, with participation from FPV Ventures. Existing investors btov Partners and Global Founders Capital, which led the company's $2.8 million seed round last year, also participated in this round.

As LatticeFlow co-founder and CEO Petar Tsankov told me, the company currently has more than 10 customers in both Europe and the U.S., including a number of large enterprises like Siemens and organizations like the Swiss Federal Railways, and is currently running pilots with quite a few more. It's this customer demand that led LatticeFlow to raise at this point.

"I was in the States and I met with some investors in Palo Alto, Tsankov explained. "They saw the bottleneck that we have with onboarding customers. We literally had machine learning engineers supporting customers and that's not how you should run the company. And they said: 'OK, take $12 million, bring these people in and expand.' That was great timing for sure because when we talked to other investors, we did see that the market has changed."

As Tsankov and his co-founder CTO Pavol Bielik noted, most enterprises today have a hard time bringing their models into production and then, when they do, they often realize that they don't perform as well as they expected. The promise of LatticeFlow is that it can auto-diagnose the data and models to find potential blind spots. In its work with a major medical company, its tools to analyze their datasets and models quickly found more than half a dozen critical blind spots in their state-of-the-art production models, for example.

The team noted that it's not enough to only look at the training data and ensure that there is a diverse set of images -- in the case of the vision models that LatticeFlow specializes in -- but also examine the models.


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