Data & AI

Multi-Modal Embedding Search with CLIP

Data & AI Pipelines diagram · made in Skemio

Multi-modal embedding search pipeline showing image and text encoders outputting into a unified vector space indexed by a vector database.
Multi-modal embedding search pipeline showing image and text encoders outputting into a unified vector space indexed by a vector database.
Open it in SkemioMake your own

What it shows

  • Contrastive models project text tokens and image pixels into the exact same vector space.
  • Cosine similarity directly scores semantic relevance between image and text vectors.
  • Image embeddings are precomputed once, keeping query latency sub-50ms.

The takeaway

Shared latent spaces let text queries match image content directly via vector dot products.

More data & ai pipelines diagrams