01
Explainable buyer-supplier matching
- Claude sits on top of the existing scoring engine rather than replacing it. The algorithm ranks, Claude articulates.
- Plain-language reasoning for why a supplier fits a requirement, grounded in the attributes the engine actually weighed.
- Mismatch explanations as well as matches, which is the harder generation problem and the one that builds confidence in the ranking.
- A ranked top-matches view that makes a shortlist scannable rather than exhaustive.
Match
Meridian Weaves, Tiruppur
Fit 0.91
Strong fit. Holds certified stock in the exact 65:35 blend and GSM you specified, ships to your destination port regularly, and has fulfilled three orders above your volume in the past year.
Mismatch
Coastal Textile Mills
Fit 0.42
Ranked low despite matching on material and price. Minimum order quantity is roughly four times your requirement, and lead time exceeds your stated delivery window by two weeks.
Explaining an exclusion is what separates a recommendation engine users trust from one they second-guess. When a buyer can see why an expected supplier did not appear, the ranking stops looking arbitrary.
