RudderStack has come a long way since our Github repo got posted on HN in 2019 (<a href="https://news.ycombinator.com/item?id=21081756">https://news.ycombinator.com/item?id=21081756</a>) and we made our first Show HN post in 2020 (<a href="https://news.ycombinator.com/item?id=22637302">https://news.ycombinator.com/item?id=22637302</a>).<p>We recently launched a new product called Profiles to solve the technical challenges around identity resolution — detailed here on our blog (<a href="https://www.rudderstack.com/blog/why-it-s-hard-to-build-a-360-degree-view-of-your-customer/" rel="nofollow noreferrer">https://www.rudderstack.com/blog/why-it-s-hard-to-build-a-36...</a>).<p>The problem is one that we are intimately familiar with. At my previous company, these engineering hurdles prevented us from shipping ML projects that had the potential to make bottom-line impact.<p>Profiles is a data unification product that allows you to specify important customer traits, then runs the joins and computations automatically, producing an identity graph, user features, and full customer 360 table in your warehouse.<p>We created a public project, called Profile Builder, that showcases much of Profile’s functionality. Check out the repo for a quickstart project that showcases the basics, and please give us your feedback.