[seanw265]

Yes certainly! I've dealt with large datasets like this in the past and know firsthand how challenging it can be to wrangle them.

Something like this would be a great fit for my travel planner app if I knew I could trust that the results were high quality before prompting the user with them.

Btw I edited my earlier comment with a few more examples just before you replied.

Good luck!

[glawrence13]

Appreciate it. FYI, for the specific bugs you flagged, looks like Nintendo was improperly named (reindexing products with that name now), and sounds like the pain point you felt was extraneous search results that really didn't belong. Transparently, the problem we're facing there is vector search can be a bit of a black box, so we're trying to tune our hybrid search to cull out really crazy results, but obviously it still needs work.

One of the ways we're combatting these search problems in the early days is developers can curate their catalog with specific brands, merchants, and categories (and even down to the product level) so you know exactly what the search space for each of your queries is. Curious to hear about your travel planner app -- if you think this would be a helpful tool, feel free to reach out at [e-mail]

[aschiff1]

Hi, we fixed this bug and you should see better results now. I'm getting good results for "men's wallet" and "plain white pillowcase". Try it out and let me know what you think!

[seanw265]

The results look much much better now. Great job.