Elliot Shmukler

So our end users tend to be kind of data scientists, data analysts, folks that are deep in the data inside these companies and many, many examples, right? But usually they'll spot, for example, oftentimes companies are pulling in third-party data, right? Instacart used to pull in grocery feeds from, you know, every inventory feeds from every grocery store that we worked with. Sometimes those feeds would be wrong, right? And Anomalo can spot those issues immediately or they're pulling in reports

So our customers point Anomalo at their data warehouse where all of their data lives. And we automatically use AI and machine learning technologies to spot issues in their data and alert them about these issues, you know, before that causes things to break, before that causes the dashboards to be wrong and bad numbers to be reported, bad decisions to be made or, you know, machine learning models that are using that data to kind of go off the rail.

And so Anomalo is kind of the tool we wish we had back in the Instacart, Welfare and LinkedIn days to catch these data issues.

Slack is similar, right? Slack had amazing growth for many years because what you want to do in Slack is once you get on Slack, well, you want your team to be on Slack, so you invite them, right?

And my favorite is actually not from Instacart, but it's what Uber did in the early days. They would send people to like sporting events, right? These huge events, right? Thousands of people leaving the stadium that all need a ride. And they're, they'd be like, do you need a ride? Here's an app you can try to get you a ride home. Wouldn't that be great? Yes. Press a button, get a ride. Right. Things that don't scale. Don't have to pick up the phone. You know, completely manual, but hugely powerf