back_office_ops · workflow
Expedia Group ML Platform builds a centralized Embedding Store Service for vector similarity search
ML teams at Expedia Group faced significant engineering and integration overhead when building vector embedding use cases, with no centralized solution for storing, managing, or discovering embeddings across the organization.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Collection creation with metadata
Users create a vector collection defined by metadata such as associated service, model, and version.
Tools used
Feast
Outcome
The Embedding Store Service provides centralized vector embedding management with reduced development time, standardized APIs, and support for batch, real-time, and on-the-fly embedding workflows across Expedia Group.
Results
Time savedReduced development time and acceleration of development and iteration
Grounding & classification
Source type: technical build writeup
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enterprise searchrecommendation systemknowledge basenamed customerproduction runtime claimedtools describedworkflow describedtravelemployee productivitytechnical build writeupback office opsdata sync enrichment