RPTune pairs learned catalog curation with post-training to lift conversational product search accuracy by up to 31.4 points across 7 real merchants
For small merchants whose catalogs fit inside a long-context window, RPTune couples an encoder–reorganizer learned catalog curator with LLM post-training using automatically generated, catalog-grounded supervision: across 7 real merchants and 100 complex conversational queries each, context curation raises exact-match accuracy by 13.5 points on average and up to 20 points across 9 frozen LLM backbones, curation alone adds 14.6 points on gemini-3.7-flash, and curation plus post-training lifts gemma-4-E4B-it from 10.7% to 31.0% EM.