Faster answers on the floor. The right revision, every time.
Industrial companies run on specifications, work instructions, maintenance history and supplier contracts spread across ERP, PLM, file shares and inboxes. KnowledgeHub makes that knowledge searchable and citable, without moving it out of the systems you trust.
When know-how lives in documents, the risk lives in the revisions
A technician asks which torque value applies. A quality engineer needs to know whether a deviation has happened before. A project manager needs to know what the customer contract actually commits you to. The answers exist, in a specification, a CAPA record, a service report or a contract rider, but finding the right one, in the right revision, takes time nobody has.
And the wrong revision is worse than no answer. Audits, certifications, customer claims and safety reviews all ask the same question: which document was in force, and who approved it?
KnowledgeHub is a governed knowledge layer above the systems you already run: ERP and MES, PLM and document control, maintenance and ticketing, quality records, contracts and shared drives. It reads structured and unstructured sources together, keeps the link to every source and version, and respects the access rules you already have.
In practice: maintenance teams get answers from manuals and service history with the exact page cited. Quality teams trace a deviation back through earlier non-conformances and the CAPAs that closed them. Engineering sees which documents a change touches before it is released. Sales and legal find what contracts and side letters commit you to, across the whole portfolio.
The same layer serves any operator with heavy assets and long-lived documentation, from production lines to networks and fleets. Experienced people's know-how is captured and reviewed before it is published, so it survives retirements and shift changes.
Deploy in cloud, private cloud or on-premises. Every answer carries its sources. Every AI step can be replayed.
Revision-aware answers
every reply cites the exact document, page and revision, so superseded instructions are flagged instead of reused.
One layer across OT and IT documentation
specifications, manuals, quality records, tickets and contracts are searched together, under the permissions you already have.
Know-how that outlasts the shift change
capture what experienced people know, review it, then publish it with the same traceability as any other source.
How a manufacturer keeps work instructions in step with engineering changes
A manufacturer with several plants runs ERP and MES, a PLM system, document control, maintenance tickets, supplier quality records and decades of PDFs on shared drives. Engineering changes are released centrally, but work instructions, checklists and training material are updated locally, and not always at the same pace.
Common pains where unstructured data and agents matter
- 01
Engineering changes do not reach every instruction
A specification is revised, but local work instructions and checklists still cite the old one.
Revision-aware search shows which documents reference a superseded version, with citations, before an auditor or a customer finds it.
- 02
Quality history is scattered across systems
Deviations, non-conformances and CAPAs live in different tools and free-text reports.
Semantic linking connects a new deviation to earlier cases and the actions that closed them, with every source cited.
- 03
Tacit knowledge leaves with experienced staff
The fix for a recurring fault exists only in a senior technician's head or an old email.
Captured know-how is reviewed and published with the same provenance as any other document.
Outcomes organisations typically target
- Fewer errors caused by superseded instructions
- Faster root-cause work, with quality history in one place
- Audit and certification evidence assembled from cited sources, not from memory
Easy to start. Safe to stop.
The pilot runs at a fixed price: we map the workflow, deploy it in your environment and prove it on your own cases. Then you decide.
Fixed price · Fixed timeframe
- 01
Map the workflow
Two weeks with your people where we document what happens today, including the parts nobody wrote down.
- 02
Deploy in your environment
Inside your tenancy, on your data residency terms, with no exports and nothing leaving through the side door.
- 03
Prove it under audit
Controlled evaluation against your own cases with compliance and the process owner signing off before go-live.
- 04
Run in production
We stay on with retraining, reporting and ongoing oversight for as long as the workflow runs.
Fixed price, Fixed timeframe. 8–12 weeks pilot: Continue (Expand once you know it works) / Stop.