Distributor · Deep parts researchThe problem
Customers know what has broken but not what the replacement is called. One writes “transistor” and means a switch. Another writes “seal” and means a gasket. Catalogue search matches words, so these enquiries return nothing.
The salesperson then investigates by hand: guess the part family, open drawings one by one, search manufacturer sites, then email a supplier. Each ambiguous enquiry took minutes to hours of research, and some went unanswered while a competitor replied.
How it works
An AI research agent handles these enquiries automatically. It processes each quote request, searches the company’s parts library and manufacturer websites, works out the likely part and returns a part number with the pages and links it used. It places the order with the supplier or manufacturer the customer specifies.
- Plain-language enquiry in, part number and evidence out
- Searches the internal library first, then manufacturer sites
- Every answer links to the drawing page or web page it came from
- Follow-up questions stay in the same research thread
The results
- Ambiguous enquiries get a checked answer the same hour instead of waiting for a supplier.
- The salesperson sees the drawing page or web page behind every answer, so no part number is quoted unchecked.
- Research that depended on experienced staff can now be done by anyone on the desk.
- Fewer supplier requests, so fewer quotes stall for days.