You put basically a MVP product out there with abnormal pricing. Your enterprise customers that are drowning in money can start using it and using that money you can grow your org by hiring more engineers. At this point you start working on adding new features and do cost optimization. Since your whole architecture was designed based on "we have to ship this ASAP", you deliver some real nice cost reduction easily. Then you reflect this to your customers and gain goodwill and good PR.
One of my colleagues asked if it might be better than creating our own infrastructure for that. I ran the numbers for one of our recent jobs, feeding a million tweets to two ML models to see which worked better. That would have cost about $1800 on Huggingface. Using AWS spot instances, it was maybe $25 for us to run ourselves.
Of course, we can do it at that price because we are paying for engineers and plan on classifying enormous amounts of text, so it works out for us. Plenty of other people probably should just use Huggingface. But I can't help looking at that 70x markup and think, "Fuck me? No, fuck you!"
Thats $24/month just to ingest the cpu/ram/diskspace data from each server. Plus storage and query costs.
At work I have a single r4.xlarge instance handling 1.3 million metrics every 15 seconds. Storage is not clustered but cost is only $500/month. It would cost me $45k/month just for the ingest with the new managed service.