AI-ready infrastructure for modern retail

1-- Get the embedding of the user's last purchased product
2LET $last = SELECT *, out.embedding AS embedding
3    FROM ONLY purchased
4    WHERE in = user:shopper_01
5    ORDER BY at DESC LIMIT 1;
6
7-- Find visually and semantically similar products
8SELECT id, name, price,
9    vector::similarity::cosine($last.embedding, embedding) AS score
10FROM product
11WHERE score > 0.8
12ORDER BY score DESC
13LIMIT 6;