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LatticeFlow secures $12 million in venture capital funding to eliminate model blind spots

The funding will accelerate development of the first scalable AI platform to automatically diagnose and fix data and model issues in computer vision, vital for enabling real-world model adoption.

The funding will accelerate development of the first scalable AI platform to automatically diagnose and fix data and model issues in computer vision, vital for enabling real-world model adoption.

Fig 1: Founding team (from left to right): Prof. Andreas Krause, Dr. Petar Tsankov (CEO), Dr. Pavol Bielik (CTO), Prof. Martin Vechev.

LatticeFlow, the only artificial intelligence (AI) platform that can automatically find and fix AI data and model errors, today announced a $12 million Series A funding round. The investment will enable LatticeFlow to expand the capabilities of its platform and respond to growing customer demand as more companies – including a number of Fortune 500 customers such as Siemens Mobility, and AI scaleups such as Intenseye, Voxel AI, and Carscan – deploy computer vision models at scale.

Today’s investment in the award-winning ETH Zurich spin-off, bringing total funding to date to $14.8 million, was led by Atlantic Bridge and OpenOcean, with participation from FPV Ventures and existing investors btov Partners and Global Founders Capital. The potential addressable market for computer vision is sizable due to its rapid adoption rate from manufacturing, healthcare, retail, security, and safety industries that are digitizing processes to become more data-driven.

In the past few years, computer vision AI models have surpassed human-level performance across image classification, detection, and other tasks in the lab. However, models often fail to work as expected when deployed in production because real-world scenarios are far more complex and varied than lab training datasets. Because of this, 90% of all models don’t reach production, resulting in billions of losses.

“We developed LatticeFlow because we knew the impossible task that engineers were up against with the pain-staking, manual process of fixing data and model issues to create AI models that work in the real world,” said Petar Tsankov, Co-founder and CEO, LatticeFlow. “At scale, it was clearly an unwinnable battle, so we focused on developing tools to help engineers work smart and automate fixes across large datasets and models.”

Automating Fixes to Data and Model Issues

The LatticeFlow platform was built to automate the process of solving data quality and blind spot issues in computer vision AI models, critical to enabling model performance in the wild. 

  • Data issues: LatticeFlow is unique in its ability to automatically discover and fix data quality issues at scale across datasets of millions of images, including labeling errors, poor-quality samples, data biases, and others.
  • Model blind spots: The platform also automates the discovery of blind spot scenarios, often impossible to spot manually, and fixes them before real-world performance is impacted. To patch the model, LatticeFlow has developed a new, scalable method for targeted data augmentation. 

“The painful truth is that today, most large-scale AI model deployments simply are not functioning reliably in the real world,” said Sunir Kapoor, Operating Partner at Atlantic Bridge. “This is largely due to the absence of tools that help engineers efficiently resolve critical AI data and model errors. But, this is also why the Atlantic Bridge team so unambiguously reached the decision to invest in LatticeFlow. We believe that the company is poised for tremendous growth, since it is currently the only company that auto-diagnoses and fixes AI data and model defects at scale.”

Ekaterina Almasque, General Partner of OpenOcean said: “If there’s one group that can make machine learning deployments at scale finally happen, it’s LatticeFlow’s team. We were hugely impressed by their amazing pedigree from academia, ETH Zurich, as well as their background as serial entrepreneurs.”

 “There’s a major bottleneck in bringing AI models built in the lab into production. Despite the exponential growth of AI models, operationalizing them is extremely hard. LatticeFlow is addressing this in a unique way with its unstructured data quality analysis and improvement. We’re excited to join the LatticeFlow journey to build a leading automation platform for computer vision deployments, thus accelerating the roll-out of AI.”

About Atlantic Bridge

Atlantic Bridge is a global technology investment firm with over €1.2 billion of assets under management across seven funds, investing in deep tech companies in Europe and the U.S. Atlantic Bridge supports portfolio companies in scaling internationally with a global investment team and offices across London, Palo Alto, Dublin, Munich and Paris. 

For more information about Atlantic Bridge, visit

About Open Ocean

OpenOcean is an early-stage venture capital firm operating across Europe with offices in London and Helsinki. With an entrepreneurial background from building several category-defining software businesses (MySQL, MariaDB, etc.), the firm empowers bold founders building global and scalable companies delivering solutions for the data-economy. OpenOcean typically leads or co-leads European €10M Series A funding rounds. Since inception, the firm has raised four funds with the latest fundraise totaling over €110m.

For more information about OpenOcean, visit

Fig 2: LatticeFlow uncovers a bias in data for training car damage inspection AI models. Since people often point at scratches, this causes models to learn that fingers indicate damage (a spurious feature). This issue is fixed with a custom augmentation that removes fingers from all images.

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