At ConcreteAI, we’re building tools to help the construction industry make faster, smarter decisions grounded in real-world data. That’s why we partnered with Precast Concrete Pte Ltd, part of Soilbuild Construction Group, to tackle a challenge that hits right at the heart of productivity: early-age concrete strength prediction.
The problem: Lab results don’t always reflect reality.
In traditional workflows, cube testing is still the go-to method for monitoring concrete strength. But here's the catch – these cubes are cured under lab conditions, not on-site ones. That mismatch leads to conservative estimates, delayed decisions, and longer cycle times. In precast production, where speed and precision are critical, this gap between test and reality creates real friction.
Our solution: Real-time, in-situ strength monitoring
We developed a compact, smart sensor system that monitors strength development in real-time, based on actual curing conditions. By replicating the in-situ temperature profile in the cube curing process, we’ve managed to reduce curing time by up to 30%, allowing for earlier formwork removal without compromising structural integrity.
That means less reliance on cube testing, faster element release, and a smoother path to using low-carbon concrete. With feedback and validation from the team at Soilbuild, we tested the system in live production environments – and proved its value.
Why It Matters
Faster formwork removal directly improves productivity. But more than that, it builds confidence in new materials and practices. With better data, we can shift away from conservative defaults and adopt low-carbon mixes without affecting timelines.
Soilbuild’s openness to innovation and access to real production conditions made all the difference. Their insight helped us shape a solution that’s not only technically sound but also aligned with real operational needs.
What’s Next
We’re scaling this across more precast elements and pushing toward full integration with production workflows. Automating these insights will make them even more usable across teams, sites, and regions. We're also working to ensure this temperature-matching approach is recognised as a valid testing method in the wider industry.
Ultimately, we’re building tools that empower faster decisions, lower emissions, and better outcomes.
The BEAMP difference
BEAMP gave us more than just a platform. It gave us direction. It connected us with the right partner, brought structure to our pilot, and gave us the space to build something meaningful.
Most of all, it helped us shape a solution alongside the people who would actually use it. That’s how innovation should be.
Yun Han (Peter) Lim
Co-founder and Head of Operations
Concrete AI
