My team has been using Pganalyze (which has its own index advisor), and honestly, it's one of my favorite technical tools ever. I don't know how you could run a large-scale postgres setup without it. In addition to index advice, it also shows top queries, vacuums, etc, and monitors for a whole host of other issues out of the box.
They also have a ton of great content on their blog (5mins of postgres) where the founder will find blog posts by different authors/companies and analyze them in depth.
For anyone interested in how pganalyze's approach compares to this extension (and other alternatives like dexter, or using HypoPG directly), I gave a talk with my colleague Philippe last year at PgCon that describes how we use constraint programming and CP-SAT for dealing with the trade-off between index write overhead and read performance improvement, across multiple queries on a table:
If anyone has some background in optimization and is interested in the more technical side of things, I gave a talk at JOPT 2023, comparing MIP and CP approaches for this problem. The slides can be found here: https://github.com/PhilippeOlivier/jopt2023
They also have a ton of great content on their blog (5mins of postgres) where the founder will find blog posts by different authors/companies and analyze them in depth.