Workflow · media · workflow
Establishing a Large-Scale Learned Retrieval System at Pinterest
Pinterest's homefeed retrieval relied on heuristic approaches based on Pin-Board graphs and user-followed interests rather than learning from actual user engagement, limiting adaptability as the platform scaled to hundreds of millions of users.
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 · User engagement event logging
The retrieval model is trained from logged user engagement events collected across Pinterest.
Tools used
ManasANN
Outcome
The learned retrieval system achieved top user coverage and top three save rates among homefeed candidate generators, enabling deprecation of two legacy generators with site-wide engagement improvements.
Results
Volumetop three save rates
Grounding & classification
Source type: technical build writeup
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