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Hub for Technical Issue Resolution
A resolution assistant for technicians and operators. Hub summarises recent work on the asset, matches ticket properties and comments against the organisation's own troubleshooting guides — including the ones that only exist as PDFs — and watches ticket trends for the failure patterns a maintenance programme should have caught.
Monitored assets
| Ticket | Asset | Fault | Opened | Match | Trend |
|---|---|---|---|---|---|
| TK-9921 | Press P-07 | Hydraulic pressure drop | 14 min | Guide HG-22 · 0.94 | |
| TK-9918 | Conveyor C-12 | Belt tracking alarm | 41 min | Prior fix TK-8830 | |
| TK-9915 | Robot R-03 | Joint 4 torque fault | 1h 05m | Guide RB-07 · 0.88 | |
| TK-9910 | Press P-07 | Sensor S-4 intermittent | 2h 20m | Repeat pattern · 3rd | |
| TK-9904 | Chiller CH-1 | Temp drift +2°C | 3h 10m | Prior fix TK-7712 | |
| TK-9899 | Conveyor C-12 | Motor overcurrent | 5h | Guide CV-11 · 0.81 |
TK-9921 · recommended procedure
- 01Recent work: seal kit replaced on P-07 (TK-9702, 11 days ago).
- 02Matched HG-22 §3.4 — check accumulator pre-charge (spec 90 bar).
- 03TK-8830 comment: 'pre-charge was 60 bar, recharged, resolved'.
- 04Pattern: 3rd pressure fault on P-07 in 30 days → flagged to maintenance.
// Problem
The Problem
When a machine goes down, the fastest route to a fix is usually something the organisation already knows: what was done to this asset last week, what fixed the same symptom on a sibling machine, and which page of which manual covers the error code. None of that is reachable in the moment. Work history lives in the maintenance system, prior fixes live in free-text ticket comments nobody indexes, and the troubleshooting guide is a two-hundred-page PDF on a shared drive. So the technician diagnoses from scratch, and the asset stays down while they do.
- Recent work on the asset is invisible at triage, so technicians re-diagnose what a colleague just fixed.
- The most valuable knowledge — what actually worked last time — is trapped in unstructured ticket comments.
- Troubleshooting guides exist as PDFs, which means they exist but are not usable under time pressure.
- Repeat-failure patterns only become visible in a quarterly review, long after the third identical ticket.
// Overview
Hub sits on the ticket queue and does the retrieval a technician would do if they had the time. On arrival, each ticket is enriched with a summary of work recently performed on the associated asset, so the operator starts from current state rather than from the symptom alone. Ticket properties and free-text comments are matched against the organisation's own troubleshooting documentation — unstructured formats included — and the relevant procedure is recommended rather than searched for. Historic comments on similar tickets are mined for what actually resolved the issue, which turns closed tickets into a working knowledge base. Running underneath, trend monitoring watches for clusters of similar tickets inside a rolling window and flags them into the preventative maintenance programme.
// AI System
Why AI
Every input here is unstructured and none of it is consistently written. Ticket comments are shorthand typed by a technician with oily hands; troubleshooting guides are scanned PDFs with tables and diagrams; the same fault is described five different ways by five people. Keyword search over that corpus returns nothing useful, which is why nobody uses it. Retrieval grounded in the ontology — the asset, its components, its ticket history — plus a model that can read the prose is what makes the archive answerable. The learning loop is the compounding part: every resolved ticket makes the next retrieval better.
// Specs
Specifications
- CONTEXT
- Recent work summary on the asset, surfaced at triage
- RETRIEVAL
- Ontology-driven over manuals and internal docs, PDFs included
- FEEDBACK LOOP
- Historic ticket comments mined for what resolved the issue
- MONITORING
- Rolling-window trend detection over ticket and error volume
- AUTONOMY
- Recommends procedures; the technician executes and closes
// Features
Features
- 01Comprehensive summary of recent work on the machine or asset, surfaced before diagnosis starts.
- 02Troubleshooting manuals and internal documentation recommended by relevance, not searched by keyword.
- 03Historic ticket comments turned into an answerable record of what actually worked.
- 04Ticket properties and comments matched against preset organisational troubleshooting guides.
- 05Similar-ticket clusters over 30- and 60-day windows flagged into the maintenance programme.
- 06Unstructured formats handled natively, so existing documentation is used as-is.
// Architecture
Architecture
RESOLUTION FLOW
Runtime · one item, left to right
- 01Ticket Intake
- 02Asset Context Assembly
- 03Grounded Retrieval + MatchingRecent WorkPrior CommentsTroubleshooting GuidesError Trends
- 04Recommended Procedure
- 05Technician Execution
- 06Comment Write-Back
dashed = the inference step, where the system exercises judgment
System stack
Data in · decisions out
01
Sources
Where knowledge actually lives
02
Ingestion
Make unstructured usable
03
Ontology
Objects and their history
04AI
Intelligence
Retrieve, match, watch
05Human
Human control
The technician stays in charge
06
Actions
Written back
Observability
Every model call traced; evals run on real cases, not anecdotes.
Governance
Entitlements enforced at retrieval; rules versioned by the organisation.
Write-back
Systems of record are written only through the approval gate.
Closed tickets return to the retrieval corpus, so the next identical fault resolves faster than this one.
// Impact
Impact
- Every ticket
- Opens with asset context attacheddesign intent
- 30 / 60 day
- Windows monitored for repeat-failure clustersdesign intent
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