Evolve the operating model.
Connect plant systems, ERP and engineering knowledge while respecting site connectivity, safety boundaries and production schedules.
Turn equipment, quality and supply-chain information into dependable operational intelligence.
Explore the opportunitiesConnect plant systems, ERP and engineering knowledge while respecting site connectivity, safety boundaries and production schedules.
Build an industrial AI product with edge-to-cloud data flows, fleet observability and a repeatable customer deployment model.
Each direction starts with a bounded workflow and an agreed measure of usefulness.
Give maintenance and engineering teams cited answers from approved manuals, service history and procedures. Route uncertain or safety-critical guidance to authorised experts.
Use voice agents for service intake, job-status updates and parts enquiries. Connect conversation outcomes to CRM and field-service tools, with human handoff for complex issues.
Connect sites to an AWS foundation with segmentation, EKS services and observable integration. Handle intermittent links and separate production control from enterprise services.
Combine equipment events, quality records and enterprise data. Engineer contextual models, quality controls and pipelines for maintenance analytics and production planning.
Safety-critical control remains inside explicitly engineered and approved control systems. AI assistance must respect plant operating procedures and change authority.
How we approach trustAWS is our first choice for cloud foundations. We bring OpenAI, Databricks and ElevenLabs into the design where their capabilities serve the workload. Integration with the customer’s existing systems remains part of the work.
A working conversation about the opportunity, the constraints and a useful first step.