Sustainability starts with smarter operations

Use only what’s needed, when it’s needed. Up to 40% water/fertiliser savings and 30–50% less energy with smarter lighting and CO₂ control. 

AI detects pests, disease, and water stress before yield loss, cutting pesticide use by up to 75% and avoiding wasted inputs and emissions. 

Unified data fine-tunes delivery, saving ~23% water on average and lowering fertiliser-related emissions. 

Test irrigation, lighting, and CO₂ strategies in a digital twin first, avoiding mistakes, saving energy, and cutting up to 30% in carbon impact. 

Coordinate machines, AGVs, and sensors in one platform, reducing downtime and idle energy. Predictive control can cut line energy waste by up to 20%. 

AI detects anomalies before failures occur, lowering unplanned downtime and avoiding the CO₂ and cost impact of idle production lines. 

 Digital twins simulate workflows and schedules in advance, reducing material scrap and errors, helping factories lower waste rates by up to 30%. 

Simulation-first rollouts and vendor-neutral integrations let plants add new robots or sites quickly, while avoiding costly re-engineering and excess emissions. 

 Warehouses spend most of their energy on heating, cooling, and lighting. Rezylix cuts idle time and optimises flows, lowering kWh per order and reducing carbon intensity. 

 By orchestrating fleets and conveyors, Rezylix eliminates empty runs and duplication, saving energy and cutting unnecessary CO₂ emissions. 

Predictive orchestration reduces mis-picks and audit errors by up to 90%, lowering wasted packaging and material use.