In production deployments at Reddit and DoorDash, Kumo's graph-embedding-based predictions delivered gains (near double-digit click-through rate increases at Reddit) on top of teams' already highly-optimized, years-refined manual feature engineering pipelines.

46:49and we've seen you know uh revenue impacting hundreds of millions of dollars um another another great client we work with is Reddit. So the advertising models on on Reddit are built on top of or are built with Kuma. Um and it was um nearly a double digit uh increase in at uh clickthrough rates. So basically the the revenue the yeah it's like unbelievable right usually an entire team you know like increases

47:20maybe 1% that accuracy year over year right because clickthrough rate >> and this is your original point about like uh you know domain expertise and like manual features like you would imagine that they've been working on this for a long time and they've kind of squeezed a lot of the juice out of that lemon but you know here comes the machine. >> Exactly. Exactly. And it's actually

47:41interesting and I mean the you know we have a great collaboration and great relationship with with Reddit team and and they're amazingly sophisticated and of course they build their own uh super optimized feature engineered pipeline and then and then the way we did we do it there actually is that we said okay let's take your data represent it as a graph and let's create embeddings for users subreddits ads and things like

48:05that. So now these embeddings actually get appended to their to their own features, right? And even with that there was there was a huge increasing the click-through rate because this signal that the neural network learn was kind of complementaryary to what the human feature engineering uh already had. So actually the the model that is in production is combined from the neural network embeddings by by graph embeddings by Kumo as well as the manual

48:36feature engineering. Uh so that's been that's been a great a great collaboration. So it's add add the recommendation clickthrough rate prediction if you want to think of it that way. you know, or have you looked at like if their manual features really make a difference? Like, is that a feel-good thing like you left them in there because they had them? Uh, or do they provide, you know, lift that's been