Workflow · workflow

Strava ML intern prototypes post search and recommendation using vector embeddings and Vertex AI

Strava users could not easily find relevant posts and content within the app, and new users lacked discovery mechanisms to connect with non-connected peers or access interesting content.

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 · Search query submitted
A user submits a search query to retrieve relevant Strava posts.
Tools used
Vertex AI matching engineGCPNLPSnowFlake
Outcome

(not stated)

Results
Volume>4 million
Source

https://medium.com/strava-engineering/amazing-summer-on-ml-team-search-recommendation-308223bb2b75

How we source this →

Grounding & classification
Source type: technical build writeup
16 fields verified against source quotes.
data extractionenterprise searchpersonalizationrecommendation systemsocial media postnamed customertools describedworkflow describedsoftwaretechnical build writeupextract classify route