London, 4th January – In a significant leap forward for geotechnical analysis, Quantas Labs, a frontrunner in AI technology, has announced the completion of a £430K seed funding round. This marks a significant milestone in their journey to revolutionize erosion impact prediction.

The funding round saw a £235k investment from Faisal Al-Rajhi, underscoring strong market confidence in Quantas Labs. This investment, coupled with contributions from various other investors, is an explicit endorsement of the company’s trail-blazing approach under the leadership of the 20-year-old founder, Alex Pourquery.

Founded and headquartered in the UK, Quantas Labs’ proprietary technology is the first of its kind in erosion prediction. Employing a unique hybrid framework combining convolutional and recurrent neural networks, this advanced system excels in processing complex geospatial and temporal data, setting a new benchmark. The technology integrates advanced geostatistical models like Kriging and Bayesian networks for nuanced spatial analysis and leverages real-time climatic data through an API-driven, edge computing enhanced pipeline. Additionally, they have developed a sophisticated soil-type classification system using hyperspectral imaging and deep learning, improving the precision of erosion predictions in diverse environments.

Quantas Labs is committed to serving a wide range of beneficiaries, from local governments and environmentalists to agricultural and construction sectors. As they embark on this exciting phase of growth, they remain dedicated to their commitment to innovative environmental solutions. This development marks not only a significant stride in the industry but also a steadfast dedication to shaping a sustainable future.

Alex Pourquery, CEO at Quantas Labs said:

“This seed funding will significantly boost our development and go-to-market strategies, accelerating our path to becoming a leader in geotechnical analysis. Our technology not only supports regulatory compliance but also sets new standards in proactive environmental management”.