Plot twist: there are no transformer models, GPU clusters, or vector embeddings here.
We built Glyph because we needed fast content intelligence for some of our own products.
Then we made it fast.
Glyph converts text into fixed-size signatures using MinHash and uses those signatures for similarity estimation, ranking, search, recommendations, guided token chain autocompletions, and document matching. Glyph runs entirely in memory, with no embedding API or vector database required.
