Start with the product you need, then extend the accumulated knowledge to other areas.
Minimal extra data entry — we build on the records you already have. From footage of everyday work and your existing records, AI organizes the know-how.
A helmet-mounted camera captures the work on video, with the operator explaining out loud.
Bring in existing failure and inspection logs, manuals, drawings and equipment alarms.
AI reads equipment, parts, processes, tasks, anomalies and records, and maps how they relate.
Equipment, processes, tasks and anomalies — connected as a knowledge graph.
When something goes wrong, follow the relationships to likely causes and fixes.
Knowledge mapDoor-mirror assembly line（Part supply〜Function test）
Build a map per line, then extend it to neighbouring processes and other lines.
* Illustrative example based on a door-mirror assembly line.
Start with any of them — the map you build carries over to the next.
Every stoppage means calling a veteran and searching scattered records.
Suggests likely causes, the order to check them, and past fixes based on equipment structure, upstream/downstream relations and history.
Veteran know-how is hard to document, and training takes too long.
Extracts steps, parts, tools and cautions from work video and narration to help build searchable illustrated instructions. Humans review the result.
Defects are found at final inspection, but tracing the cause is slow.
Relates process, materials, machine conditions, inspection and change history to show candidate causes and impact scope.
High-mix, exception-heavy processes resist robot adoption.
Organizes work video, procedures and process data to select automatable tasks and supports data prep, deployment and operation.
The four products are a starting point. On the same knowledge map, we develop and deploy AI tailored to each factory.
Beyond keyword search, we trace relations among equipment, tasks, parts and causes, and present related equipment and processes as candidates for investigation.
Until now
Think of keywords, search documents, open them one by one and compare.
Knowledge map
Start from the symptom and follow the relations to likely causes and fixes.
* Showing a relation does not prove causation. Final judgement is made together with on-site checks.
Collect and structure work, equipment, anomaly and recovery data.
Support maintenance, training and quality with the map.
Reuse the same knowledge for planning, changeovers and ramp-up.
Link with line AI agents, subject to safety validation.
* Durations are indicative and depend on plant size and scope. Includes future vision (hypothesis); timing and scope are not fixed.
What may be filmed, where data is stored, access rights and how we connect with your IT/OT environment are agreed with you during onboarding.
Security FAQ →We will help you decide which line to start with and what your existing data can do. Free of charge.
