Capture Knowledge with a Smart Management System

Capture knowledge means recording, structuring, and preserving what people know so it can be reused by the organization. In manufacturing, this often includes senior operator techniques, troubleshooting paths, shift notes, equipment history, and informal workarounds. Myto captures that expertise while operators work, then turns it into SOPs, diagnostics, handovers, and AI-ready operational intelligence.

The best knowledge management system depends on where knowledge is created and how teams need to use it. For manufacturing, Myto is built around the factory floor, not office documentation. It captures physical work through AI glasses, ingests operational data, generates SOPs, supports troubleshooting, and activates knowledge through AI agents inside frontline workflows.

Myto uses wearable AI glasses to capture work as operators perform it normally, so teams do not need clipboards, extra forms, or post-shift documentation sessions. Video, audio, and workflow context are structured automatically into reusable knowledge assets. This helps preserve expert judgment without interrupting production or asking frontline teams to change how they work.

Yes. Myto’s AI SOP generation engine turns captured operator expertise, machine history, logs, tickets, and existing documents into clear, version-controlled SOPs. Instead of relying on outdated PDFs, teams can create procedures based on how work is actually performed today across machines, shifts, and operators, making documentation more useful for training and daily execution.

No. Myto is designed to sit on top of systems like MES, CMMS, SCADA, EAM, and ERP platforms rather than replacing them. It reads and connects operational data through a manufacturing lens, linking tickets, work orders, machine history, SOPs, and captured frontline knowledge into an intelligence layer that supports operators and AI agents.

Myto is delivered as enterprise SaaS with fast setup, minimal IT lift, and no heavy infrastructure requirement. Deployment scope depends on plant count, integrations, AI glasses headcount, and workflow complexity. The platform is built for frontline usability from day one, so operators can begin capturing knowledge without navigating complicated new systems.

Myto can ingest SOPs, machine logs, maintenance tickets, equipment history, MES and SCADA data, CMMS and EAM records, ERP work orders, quality-management data, and shift-handover notes. The system connects these sources to machines, workflows, and troubleshooting paths, creating a manufacturing knowledge base that becomes more valuable as new data flows in.

Myto uses enterprise SaaS subscription pricing that varies by the number of plants, AI agent volume, integrations, and AI glasses headcount. A discovery call helps define the deployment model, operational priorities, and quote. This structure lets manufacturers start with the workflows that matter most and expand as the knowledge layer compounds.