Concrete.ai Launches Concrete Copilot: GenAI Solution Saving Users Millions and Slashing Carbon Footprints by 30 Percent

The patented AI platform develops optimized concrete mix designs and predicts performance within seconds, empowering concrete producers to rapidly select the most optimal concrete recipe for any application

Concrete.ai, the company using GenAI to optimize concrete mix designs for efficiency, carbon, and cost savings, announced the commercial availability of its field-tested, patented AI platform, Concrete Copilot. From the millions of possible mix designs, the platform generates those that are the most optimized for any combination of cost, performance, and carbon reduction, empowering producers to select the best mix for their use case.

Mix optimization is crucial to any concrete producer’s success, but the design process has become increasingly difficult with today’s complexity of supply chains, constant changes in material types and costs, and the vast array of complex performance data. And with a growing number of policies mandating low-embodied carbon material for construction projects, there is additional urgency for builders to reduce their carbon footprint, specifically within concrete production – which is responsible for 9% of worldwide emissions.

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Producers are often left struggling to not only identify the right concrete mixes that meet requirements but also to introduce them into production quickly without disrupting plant operations or affecting performance and cost.
During Concrete Copilot’s extensive field testing with producers across the US, the platform optimized mix designs used in over 2,000,000 cubic yards of concrete – enough concrete to fill 681 Olympic-size swimming pools. The average material savings were $5.04/cubic yard, and the average carbon reduction was 30%. For most producers, these results were seen within just one month of activating the platform.

“I’ve spent 26 years working in the construction and ready mix industries and personally know the challenges concrete producers have to overcome to find the most economically viable mix designs,” said Alex Hall, CEO of Concrete.ai. “We built Concrete Copilot, so producers don’t have to choose between cutting cost and carbon. Our ultimate goal is to reduce the annual global carbon footprint of concrete by ~500 million tons just by optimizing concrete mixes with materials already in supply chains.”

Here’s how it works: Concrete Copilot first integrates with a producer’s current and historical data. Producers can select their optimization criteria based on their specific objectives. The platform then creates millions of mix designs in seconds and presents the optimal one to the user to approve or modify based on their judgment and experience, streamlining the design process from months to minutes.

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Concrete Copilot uses the materials in a producer’s current supply chain, and when there are shifts in a material’s availability or cost, producers can rapidly create new mix designs. The platform also allows for quick evaluation of the many new sustainable materials entering the market each year, helping them to enter production quickly for an immediate environmental impact.

“Integrating Concrete Copilot into our existing software was a remarkably quick and smooth process. Using our own data and local materials, the tool efficiently streamlined our mix design process, allowing us to maximize materials cost savings and deploy the optimized mix designs into production faster,” said Chris Rapp, Vice President and General Manager of VCNA Prairie Materials. “This resulted in significant reductions in cost and carbon footprint.”

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