Following the close of our sourcing period on 20 August, we are delighted to announce the start-ups selected to progress to the next stage. We received 60+ applications from 26 countries across six continents, which were evaluated by a panel of more than 80 experts from the cement and concrete industry. The selected start-ups have now been invited to pitch their solutions to our member companies, with the opportunity to connect, collaborate and form consortia.
We’re excited to introduce the start-ups moving forward and wish them the very best of luck!
Aignosi’s SIENTIA™ provides an industrial AI platform optimizing cement processes, energy use, clinker factor and CO₂ emissions.
Alcemy provides an industrial AI platform helping cement producers optimize clinker, energy use and decarbonisation.
Carbon Negative Solutions uses AI to optimize SCM blends from local minerals and industrial byproducts, reducing cement content and emissions.
Cloud Cycle uses IoT and AI for real-time concrete monitoring, reducing cement overdesign, costs and CO₂.
Concrete.ai uses generative AI to design low-carbon concrete mixes meeting performance, cost and regulatory requirements.
Concreto 4.0 uses AI to optimize concrete production, reducing cement overuse, clinker consumption and CO₂ emissions.
Converge uses AI and IoT to optimize lower-carbon concrete mixes using plant and jobsite data.
EcoMetrix uses AI to optimize concrete mixes for strength, cost and clinker substitution, reducing CO₂ emissions.
EcoStruct combines AI, quality assessment and sensors to reduce cement overdesign, waste and CO₂ emissions.
Faclon Labs uses Industrial AI to optimize cement plant energy, reliability, alternative fuel use and CO₂ emissions.
Gigaton uses AI-based control and optimization to improve cement pyroprocessing, alternative fuel use and energy efficiency.
Greenovative develops an AI-driven energy intelligence platform that optimizes energy sources and plant consumption in cement plants to reduce energy costs and carbon emissions.
Gulf Organisation for Research and Development (CEMENTO-AI) uses AI to predict clinker quality and cement strength in real time, improving efficiency and reducing resource use.
Juna AI uses agentic AI to optimize cement plant operations, scheduling, energy efficiency and CO₂ performance.
Matom.AI uses multimodal AI to optimize kiln combustion, alternative fuel use, energy efficiency and clinker quality.
NWarchAI uses edge-AI computer vision to optimize kiln operations, alternative fuel use and clinker quality.
oPRO.ai uses deep-learning AI and real-time process optimization to improve cement production efficiency, reducing fuel consumption, CO₂ emissions, and operational instability.
Rapid Analytix combines rapid material testing and AI to optimize concrete mixes and accelerate lower-carbon material adoption.
Tikal Industries converts industrial waste into SCMs that can replace significant amounts of Portland cement.
Uptime Analytic uses a physical-AI digital twin to optimize clinker kilns, reducing energy use and CO₂ emissions.