The future of concrete engineering requires better intelligence.

  • Fragmented datasets across materials, suppliers, and testing workflows
  • Increasing more complex trade-offs between performance, cost, and emissions as new materials are introduced in the market
  • Growing pressure to accelerate low-carbon innovation at scale

Turning Material and Sustainability Data Into Smarter Decisions

ACORN uses agentic AI to develop optimized low-carbon concrete mixes across performance, cost, climate impact, and engineering constraints.

Combining material science, machine learning, and engineering expertise, ACORN accelerates the development of high-performance concrete recipes for real-world production environments while maintaining strict confidentiality for proprietary data and models.

Designed for the next generation of intelligent concrete engineering.

Data-driven

Handles large, structured concrete datasets efficiently

AI-Powered Models

Accurate predictions using domain-informed AI

Multi-Objective Decision Support

Balances strength, cost, and carbon footprint

Practitioner-Friendly Interface

Easy interface for engineers to assess mixes quickly

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NEWS AND ARTICLES

  • ”Concrete Action Towards Net Zero” Episode 4 – Building the Transition: How Construction Leaders Choose Low-Carbon Materials
    ”Concrete Action Towards Net Zero” Episode 4 – Building the Transition: How Construction Leaders Choose Low-Carbon Materials
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    When discussing sustainable construction, procurement often takes center stage. The focus is usually on selecting low-carbon materials, evaluating suppliers, and reducing emissions through purchasing decisions. But what if the biggest opportunity to reduce a building’s climate impact comes long before procurement begins? In this episode of Concrete Action Towards Net Zero, Anders Enebjörk (profile link),…

  • From Clean Data to Business Value: Where Machine Learning Actually Delivers
    From Clean Data to Business Value: Where Machine Learning Actually Delivers
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    Now that the data is cleaned and ready, it is easy to assume the hard part is done. The model will perform well, predictions will be accurate, and value will naturally follow. That assumption is where many projects fall short. You feed the data, train the model, and generate predictions, but a prediction on its…

  • ”Concrete Action Towards Net Zero” Episode 3 – From Pilot to Scale: How Swerock made green concrete standard
    ”Concrete Action Towards Net Zero” Episode 3 – From Pilot to Scale: How Swerock made green concrete standard
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    Every cubic meter of concrete counts. At Swerock, part of the PEAB Group in Sweden, reducing CO₂ emissions is not a bold announcement, it is a series of small, deliberate steps. Staffan Carlström, Product Developer at Swerock, explains how testing, learning, and scaling eco-concrete has enabled measurable progress project by project and dataset by dataset.…