recommendation-engine
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Netcore Unbxd and the sale hiding in your search bar
A shopper asks for drinks for teetotallers. The catalogue speaks in SKUs. Netcore Unbxd makes its living translating between the two.
The Four-Day App That Taught Podcasts to Answer Back
Castbox started as a holiday-weekend Android experiment. Its lasting bet was stranger and more useful: if every spoken sentence could become an index, a podcast library could behave less like radio and more like the web.
GraphDive Tried to Make the Web Less Stupid. Then Facebook Was the Ground Beneath It.
GraphDive could infer your income, interests and relationship status from the trail you left on Facebook. The clever part was the graph. The useful part was learning that enterprise customers will still punish an unfinished feature and undervalue free work.
The Insurance Broker That Turned Itself Into an API
Born inside the world's largest independent broker, Mylo spent a decade turning insurance advice into software other companies can plug in. Here is how a Kansas City team quietly became the insurance layer behind small-business platforms.
Netflix
Netflix escaped the red-envelope era by learning to replace its own best idea. Now it is turning a streaming subscription into a wider entertainment system - one built from stories, software, live moments, games and advertising.
TigerGraph
TigerGraph is a Redwood City-based software company building a native, massively parallel graph database and analytics platform designed to find patterns across deeply connected data in real time. Founded in 2012 by Dr. Yu Xu, it powers fraud detection, anti-money laundering, customer 360, recommendation engines and, increasingly, the relationship-intelligence layer behind enterprise AI and GraphRAG. Its cloud-native platform, TigerGraph Savanna, lets organizations query trillions of edges with the GSQL query language across AWS, Azure and Google Cloud.
Preferabli
Preferabli is an AI-driven B2B2C product discovery and recommendation software platform for wine, beer, spirits and other sensory consumer products. Formerly Wine Ring, the company pairs proprietary, patented machine-learning models with the world's largest assembled group of Masters of Wine and Master Sommeliers to predict what an individual will actually like - then plugs that prediction into retailers, hotels and merchants across roughly 100 countries.