Concrete-AI, a data science company, announced it has raised $2 million in a seed financing round with participation by the Grantham Foundation for the Protection of the Environment, a prominent family office and other marquee investors. This financing will accelerate the rollout of Concrete-AI’s pioneering data science platform that uses artificial intelligence (AI) and machine learning (ML) to optimize supply chains and materials selection to bring new efficiencies to the design, proportioning and production of concrete mixtures.
Concrete-AI said its “platform delivers unparalleled reductions in the cost and embodied carbon of ready mixed and precast concrete used in construction, without any changes in their method of production, the materials used or anything else.”
In addition, the company announced that industry veteran Ryan Henkensiefken has joined the company as vice president of business development. Henkensiefken has spent more than a decade in the concrete and chemicals industries. Most recently, he served as market development manager for Master Builders Solutions (previously, BASF Construction Chemicals). Prior to this, he held business development, and engineering roles for Central Concrete Supply, a unit of U.S. Concrete.
During pre-commercial piloting with several of the largest cement, concrete and chemical admixtures manufacturers, including Summit Materials; U.S. Concrete, a Vulcan Materials Company; and Votorantim Cimentos (Prairie Material), Concrete-AI’s platform has been shown to reduce the material costs and embodied carbon footprint of ready-mixed concrete (RMC) by up to 10%, and up to 50%, respectively.
It achieves these reductions by applying AI/ML-enabled concrete optimization to predict the performance of concrete as a function of its mixture proportions, and the characteristics of coarse and fine aggregates, supplementary cementitious materials (SCMs), and the chemical admixture type and dosage, etc.
The result is a highly optimized, cost-effective concrete that fulfills all engineering performance characteristics such as slump, set time and strength, while utilizing locally available raw materials to ensure safety, longevity and code-compliance.
Concrete-AI said its AI/ML approach for concrete proportioning “helps solve some of the biggest challenges facing the industry: concrete overdesign; the embodied carbon footprint from cement (i.e., the glue or “binder” that holds the aggregates together to make concrete); increasing material cost; and reducing margins.”
Traditionally, because it has been difficult to predict how the constituents of a concrete mixture will affect its performance, concrete formulations have been overdesigned such that they contain excess cement.
In the United States alone, this overdesign costs the industry more than $1 billion annually, and results in 10 million tonnes of incremental carbon dioxide (CO2) emissions associated with cement production. If Concrete-AI were adopted globally carbon emissions from cement and concrete production could be reduced by 500 million tonnes per year.
“Concrete-AI offers the construction sector a one-of-a-kind, capital-light, rapidly deployable, Software-as-a-Service (SaaS) solution that brings new performance and sustainability efficiencies to concrete production while leveraging existing supply chains, manufacturing processes, and the power of data,” said Alex Hall, CEO of Concrete-AI. “To reduce the embodied carbon footprint of concrete construction projects, we must use materials effectively and efficiently. Concrete-AI enables this while ensuring safety, peak engineering performance and sustainability by optimizing the use of cement, aggregates, and diverse SCMs in concrete, in an unparalleled manner by a data-driven approach. At a time when states and the federal government are increasingly requiring and incentivizing the reduction of embodied carbon in the built environment, Concrete-AI offers the industry the leading data-driven solution for ensuring cost-effective and sustainable construction.”
The core Concrete-AI technology was developed at UCLA’s Institute for Carbon Management (ICM) by Gaurav N. Sant and Mathieu Bauchy. Sant and Bauchy are faculty members in UCLA’s Samueli School of Engineering in the Departments of Civil and Environmental Engineering. Sant is also a faculty member in the Department of Materials Science and Engineering and is the director of UCLA’s Institute for Carbon Management.