LatticeFlow raises $12M to fix AI data and model errors

The ETH Zurich spin-off, founded in 2020, built an artificial intelligence platform that can automatically find and fix AI data and model errors. The startup has today announced a $12 million Series A funding round to expand the capabilities of its platform and respond to growing customer demand as more companies deploy computer vision models at scale.

Atlantic Bridge and OpenOcean led LatticeFlow’s financing round with participation from FPV Ventures and existing investors btov Partners and Global Founders Capital. The new investment brings LatticeFlow’s total funding to $14.8 million. The capital will accelerate the development of the first scalable AI platform to diagnose and automatically fix data and model issues in computer vision, which is vital for enabling real-world model adoption.

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.

Zurich-based LatticeFlow addresses these challenges with a platform that automates the process of solving data quality and blind spot issues in computer vision AI models, critical to enabling model performance in the wild. For Data issues, LatticeFlow can automatically discover and fix data quality issues at scale across datasets of millions of images, including labelling errors, poor-quality samples, data biases, and others. Regarding 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.

“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 an unwinnable battle, so we focused on developing tools to help engineers work smart and automate fixes across large datasets and models.”

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. LatticeFlow has already secured a share of the market with customers, including Fortune 500 companies such as Siemens Mobility and AI scaleups such as Intenseye, Voxel AI, and Carscan.

(Press release/RAN)