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Runs on Opero
- AI Chat
- Knowledge autocapture
- Document processing
Diagnose a fault in the agent, identify the right SKU, generate the order — purchase orders, warranty checks, stock validation all built in.
Wrong-part returns on industrial spares are high enough to appear as a named line item on dealer P&Ls. The catalogue is rarely the problem. The seam that fails is between what the technician thinks failed and what the catalogue calls that failure — and closing it by hand, across OEM part numbers, regional SKU variants, and supersession chains, takes longer than the repair itself.
The technician describes the symptom. The Knowledge Agent narrows to the likely failed component using model and serial scoping, the same way it handles any diagnosis question. The parts module takes that identification and pre-fills the order: right SKU, right cross-reference, right OEM catalogue, right warranty and contract treatment.
Dealer-stock-aware means the system checks your warehouse before drafting the order. It does not promise next-day delivery from a location that does not hold the part. If stock is absent, it routes to the next-nearest warehouse or flags for supplier order — the parts manager sees the full picture before a commitment goes out.
Cross-reference and supersession are handled at retrieval time, not at order time. When a part number has been superseded across OEM catalogues or carries a different regional SKU, the agent resolves the correct current number before the PO is drafted. A parts manager who has hand-corrected supersession errors knows what that step is worth.
A Nordic forklift dealer. A counterbalance forklift in for a standard service. The technician describes hydraulic creep on the lift cylinder — slow drift under load, audible hiss at full extension.
The Knowledge Agent narrows the diagnosis to the tilt-cylinder seal kit, scoped to the cylinder variant fitted to that chassis by model year. The parts module pulls the SKU — in this case a kit with four line items across two sub-assemblies — confirms one unit in dealer stock, then checks the customer’s contract: paid maintenance agreement, in warranty for parts, no co-pay on seal kits under this service interval.
The agent drafts a PO with the correct line items, the contract reference, and the stock location attached. The parts manager reviews it, adjusts the labour line, and approves. The PO goes out signed by a human in under a minute. Nothing about that minute required the parts manager to open the OEM catalogue, call the warehouse, or look up the customer contract separately.
Dealers who deploy parts ordering alongside the Knowledge Agent report first-time-right rates improving by 20–35 percentage points in the first quarter — measured as orders that did not generate a return, a re-order, or a warranty dispute. The range is wide because it depends heavily on catalogue quality at the start. The Nize Equipment deployment follows a similar pattern; their parts pilot is described in the full case study.
Whether the agent places orders unattended: default is no. Every PO draft requires a named human to approve before it is transmitted. That is not a limitation — it is the cost-of-error gate. A wrong part ordered at scale is more expensive than the seconds it takes a parts manager to confirm.
Per-line confirmation thresholds, spend limits, and which warehouses count as in-stock are all configurable per dealer location. Which customers see which catalogues — OEM-only, multi-brand, preferred-supplier — is access-controlled at the customer level, not the catalogue level. Every order draft and every approval action is written to the audit log with timestamp and user.
ERP connections cover SAP, IFS, and Microsoft Dynamics as the stock-of-record source. OEM parts feeds — where the catalogue lives — connect directly; the agent does not re-key part numbers from a PDF. Dealer warehouse-management systems provide real-time stock counts. When the warehouse system your operation uses is not on the standard list, it connects through the same integration layer that handles the rest of the corpus. Full connector list at Integrations.
Runs on Opero
Runs on Opero
Runs on Opero
Runs on Opero
“It genuinely works. When I chat with it, I get the knowledge I need — instead of calling the office and asking a hydraulic engineer. When it comes to solving a specific problem…”
Runs on Opero
“A technician with limited product knowledge found the right solution through the Opero AI agent and resolved the issue without interrupting a colleague who was out with customers…”
Runs on Opero
Runs on Opero
Runs on Opero
“It is a true pleasure collaborating with Opero, who deliver AI solutions of the absolute highest quality. Their deep technical expertise combined with a fantastic understanding of…”
Runs on Opero
Runs on Opero
Runs on Opero
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