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E-commerce

Crowdery

Crowdery is an online platform, allowing its users to vote on their favorite product design out of a set. It then builds its users a personalized marketplace of their top picks, and top products are opened for them to pre-order at a discount. Crowdery was launched in 2013 by Maran Nelson and Aditya Viswanathan. It is based in Mountain View, C.A.

sources
2
Evidence entries preserved.
affiliations
2
Andreessen Horowitz, Y Combinator
competitors
6
Mapped from High Signal graph features.
status
generated
D1 lookup
last updated
2026-07-15
16:41 UTC
source evidence
Why this company exists here

Y Combinator

yc-company-directory #899

Crowdery is an online platform, allowing its users to vote on their favorite product design out of a set. It then builds its users a personalized marketplace of their top picks, and top products are opened for them to pre-order at a discount. Crowdery was launched in 2013 by Maran Nelson and Aditya Viswanathan. It is based in Mountain View, C.A.

source

Andreessen Horowitz

a16z-investment-list #230
source
generated read
High Signal interpretation

Crowdery is classified as E-commerce from source descriptions and fund-directory context. Similar companies below are ranked from offline product facets and meaningful description overlap; category and source affiliation can only strengthen an existing product match. For lookup-created rows, the profile starts as pending enrichment until deeper source collection runs.

offline extraction
Product facets
top productsusers
mapping method
Similarity graph

Local clusters rerank extracted product concepts and description terms. The generated graph remains the fallback for sparse descriptions: offline reciprocal product-similarity graph: extracted concepts + description terms + bounded category/affiliation boosts. Minimum fallback score: 0; max competitors: 6.

discovery cluster

Companies similar to Crowdery

E-commerce · 6 peers

A deterministic local cluster built from offline product facets and meaningful description terms. Category and selected-institution affiliation provide bounded tie-breaks. Open any peer to continue exploring its cluster.