Maintenance work held back innovation. DiMuto now trains defect models 35% faster, using agents to cut through complex trade paperwork.
An agri-food trade platform addresses the 20-30% of global food production lost to waste by tracking individual produce items across the supply chain from packhouse to retailer.
Critical data and machine learning workloads were siloed in a fragmented hybrid environment, slowing down the training of defect-detection models....
“Our setup was reliable but increasingly fragmented. To move faster, we needed to unify model training, orchestration, and monitoring. We wanted to bring everything into one ecosystem so we could focus on refining our AI rather than managing infrastructure.”
Agrifood trade platform for supply chain traceability and trade finance.
Routine code and junior support bogged down leads. AI now lets juniors work independently, freeing seniors for complex architecture.
HR spent hours resolving complex pay queries. Now, an AI copilot explains individual variances and deductions instantly.
Sonar review meant checking raw footage frame by frame. AI now scans hours of data to pinpoint targets for recovery.
Fragmented server data bottlenecked scaling. A unified model cut hardware SKUs by 50% and eliminated dozens of manual processes.