Thousands of SKUs across makes, models, model years, and supersession chains. AI part matching resolves OEM, aftermarket, and universal numbers from a plain-English description.
Every industry has its quirks. Here are yours.
We've mapped the operational quirks of automotive & parts against Nautilus capabilities. Each challenge here pairs with how we handle it.
SKU explosion
The same brake pad comes in 40 variants across different makes, models, and years. Picking the wrong one is costly and embarrassing.
AI part matching
Describe what you need in plain language. Nautilus finds the right SKU across all numbering systems instantly, with vehicle-fit filtering applied where available.
Cross-referencing
OEM numbers, aftermarket numbers, and universal part numbers all refer to the same item. Or different items. Either way, your staff has to know which is which.
Cross-reference database
Link OEM, aftermarket, and universal numbers together. One scan shows every way to identify that part, and history preserves the original number used at sale.
Core returns
Remanufactured parts require core tracking. The old part comes back, gets credited, and re-enters inventory. Mistakes here compound.
Core management
Track cores in, cores out, and credit status. Automated reconciliation catches discrepancies before they compound into a quarterly write-off.
From dock to door.
Every action a automotive & parts warehouse takes, mapped to a Nautilus flow — running on phones, tablets, or rugged scanners.
Inbound receipt
Scan against PO with cross-reference matching across OEM, aftermarket, and universal part numbers.
Velocity putaway
Fast-movers go to forward pick; slow-movers to deep storage. Cores route to the dedicated core area for credit verification.
Catalog-driven pick
Counter calls or web orders resolve through AI part matching. Picker confirms the right SKU and the right variant for the vehicle.
Counter or ship
Hand to counter customer with sale logged, or pack for delivery to dealer or installer with tracking pushed back to the originating channel.
What customers see.
Averages across Automotive & Parts customers in their first 12 months.
Automotive & Parts questions, answered.
The questions buyers in automotive & parts ask before they sign. If yours isn't here, the team can answer it on a discovery call.
How does AI part matching resolve OEM vs. aftermarket numbers?
Each SKU in Nautilus can carry multiple part-number aliases: the OEM number, the aftermarket equivalent, the universal cross-reference, and your own internal SKU. The catalog search resolves any of them to the canonical record. When a counter person describes 'brake pads for a 2018 Ford F-150,' the search returns the catalog matches with vehicle-fit filtering applied, OEM and aftermarket options side by side.
Can core returns be tracked back to original purchase orders?
Yes. Cores return scans against the original sale or a generic return queue. The credit posts to the customer's account, the core re-enters inventory tagged with its source (which sale, which date), and remanufacturing routes to the appropriate vendor. Discrepancies (cores returned without a matching sale) flag for counter-staff review rather than auto-processing.
What about supersession chains — when a part number is replaced by a newer one?
Supersession data lives on the SKU record. When a customer asks for the old part number, the catalog returns the current supersession with the substitution noted, and inventory pulls from the current part. Historical sales reports preserve the original part number for warranty and service history; current inventory reports show the superseded SKU consolidated into the active one.
Will it integrate with our parts catalog software?
Yes. Direct integrations to PartsTech, WHI Solutions, and PartsAuthority are first-party. The catalog provides the make/model/year fitment data; Nautilus provides the inventory and pricing layer. For other catalog software, we have a webhook-and-API bridge with about a week of mapping work during setup.
See Nautilus running in a automotive & parts warehouse.
Live demo with a warehouse engineer. 30 minutes. We bring the data, you bring the questions.