Industries · Connected operations that anticipate failures
AI for Manufacturing
From industrial operations to intelligence that anticipates, decides and acts.
Where AI applies
Quality, maintenance, production, planning, supply, logistics, operational safety and supplier management.
The core journey
- Operational event
- Diagnosis
- Technical knowledge
- Action
- Validation
- Learning
The transformation
A non-conformity stops being just a quality record. It can start an assisted investigation, check equipment history, find the applicable procedures, recommend actions and prepare maintenance or inspection orders, connecting sensors, reports and procedures without replacing deterministic and industrial-safety controls.
How Onni builds it
Builder structures diagnosis, investigation, planning and execution capabilities. Atlas relates assets, processes, procedures, rules and evidence. The bus connects ERP, MES, CMMS, IoT platforms and industrial systems within operational-safety boundaries.
- IoT
- Domain Knowledge
- Agents
- Events
Expected impact (indicators to track)
- Fewer unplanned stops
- Faster failure investigation
- Better quality, less rework
- More use of technical knowledge
- Better maintenance planning
- Traceable non-conformities
Expected benefits and the indicators we recommend tracking, not results of a specific deployment.
Questions this industry asks
- How do you connect AI to industrial systems?
- When should you use specialized models?
- How do you turn technical knowledge into proprietary intelligence?
- When agents, when deterministic automation?