AI Workflow Automation
Deploy agentic AI agents that automate, remediate, document, and follow up on operational work directly inside manufacturing workflows without forcing operators into another application.
Myto helps manufacturers turn frontline expertise, machine history, SOPs, and shift activity into AI-powered operational intelligence. Built for plant leaders, maintenance teams, and operators, the platform captures work hands-free, automates documentation, speeds troubleshooting, and helps keep production moving without replacing your MES, CMMS, SCADA, or ERP systems.

AI-powered tools that capture, structure, and activate factory knowledge across production, maintenance, training, and handovers.
Deploy agentic AI agents that automate, remediate, document, and follow up on operational work directly inside manufacturing workflows without forcing operators into another application.
Surface the right SOP, machine history, diagnostic checklist, and likely root causes when operators or maintenance technicians face equipment problems on the floor.
Use wearable AI glasses to record physical-world expertise as operators work, turning tribal knowledge into structured SOPs, troubleshooting flows, and training content.
Ingest SOPs, logs, tickets, MES, SCADA, CMMS, EAM, ERP, and quality data into a manufacturing knowledge layer that compounds over time.
Automatically create audit-ready, version-controlled SOPs and work instructions from captured operator expertise, machine history, tickets, and real operational workflows.
Replace clipboard and whiteboard handoffs with AI-generated shift summaries covering what ran, what broke, what was fixed, and what needs attention next.
Myto gives manufacturing teams a practical intelligence layer for day-to-day operations. It captures undocumented expertise, connects disconnected plant systems, and powers AI agents that help troubleshoot issues, generate documentation, coordinate handoffs, and support frontline decisions. The result is faster diagnosis, stronger standardization, and a knowledge base that grows as your operators, machines, and workflows keep producing new context.

Myto is built for real factory work, not just another dashboard.
AI glasses capture expertise while operators keep working normally, with no added paperwork.
SaaS deployment requires minimal IT lift and no heavy infrastructure replacement.
Simple operator experience supports deskless teams from the first day of use.
The platform grows stronger as it learns from factory systems and frontline activity.
A manufacturing AI team built for frontline operations.
Myto was founded to bridge a critical gap in manufacturing: frontline teams still depend on outdated binders, disconnected systems, and knowledge that lives only in experienced operators’ heads. The founders saw firsthand how much operational expertise disappears when senior workers retire or move on, and built Myto to capture that knowledge before it walks out the door. Combining experience from Mercedes-Benz, BCG, and Stanford, Myto brings together wearable capture technology and agentic AI automation to learn how the best operators actually work. Its vision is to give frontline workers tools as intelligent as the products they build, while helping manufacturers standardize workflows, reduce downtime, and preserve institutional knowledge.
Manufacturing operations management software helps production teams coordinate the work that keeps a plant running: procedures, maintenance activity, shift handoffs, troubleshooting, training, and operational knowledge. Myto focuses on the frontline layer by capturing real operator workflows, connecting plant data, and using AI agents to surface context, automate documentation, and support faster decisions.
Talk with Myto about your plant workflows and AI use cases.
Supported by a leading startup accelerator
Backed by a prominent technology investor
Experience from Mercedes-Benz, BCG, and Stanford
Share your plant goals, downtime challenges, and workflow priorities. Myto will help map the right AI operations approach for your team.
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