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We are also 100% customer-funded. AWS makes sense for us for the enterprise version of Geocodio where we are SOC2 audited and HIPAA-compliant.

We are primarily using Hetzner for the self-serve version of Geocodio and have been a very happy customer for decades.


Hahaha. I'll update the post once I hear back from them. One could hope that they might consider an account credit.


That was truly my hope with this post! Glad to hear that


Haha, yep we were lucky to catch this early! It could easily have gotten lost with everything else in the monthly AWS bill.


There's a couple of great open source projects[1][2][3] that try to keep up-to-date lists of domains that belong to disposable email providers.

I would probably not recommend implementing a whitelist for blocking purposes. But perhaps domains on a whitelist could get a slight scoring bump.

[1] https://github.com/disposable-email-domains/disposable-email... [2] https://github.com/disposable/disposable [3] https://github.com/unkn0w/disposable-email-domain-list


As for abuse, I made myself a tool to give myself quintillions of email addresses (not using plus addressing) on gmail.com

I use this to sign up for a service with a unique email that is basically my junk box, but the email is its own unique entry in my password manager


Thanks for giving it a read!


We are mainly B2B so we don't really see signups using Apple's email relay. That said, it could be something we might have to consider blocking in the future if it becomes a problem.

For paying customers, it probably doesn't make a lot of sense to use an anonymous email address, since we ask for your name and billing address either way (have to stay compliant with sales taxes!)


Isn't it nice to have just a little bit of an illustration instead of just text? Obviously an AI-generated image is going to spit out some nonsense text as part of the graphic, but we're not really trying to hide that it's AI generated.


I think things that require high credibility and have a learned readerbase it'd be better to not give a careless image, even at the cost of a cool image. I wouldn't mind an almost right image on some advert for cleanex or intranet holiday reminder mail, but I would be very concerned if it was used as part of EU directive


I would love do a more in-depth talk about this at some point with some more concrete examples.


Not at this time. Some simple heuristics go a long way and also makes it very easy to test and debug the logic.


I’ve seen fraud detection used in a SaaS product, and the great thing about a weighted rules approach, is professional services can understand it well enough to adjust it without help from engineering or data science, and they can explain to customers how it produced the results it did in a particular case, and the tradeoffs of adjusting the weights or thresholds, and the customers can understand it too. Whereas, a machine learning model, is much harder to understand and adjust, so issues are much more likely to be escalated back to engineering.

(This isn’t protecting the SaaS vendor against abusive signups, it is a feature of the SaaS product to help its customers detect fraud committed against themselves within the SaaS product’s scope.)


I once did a machine learning project at Intel. The end result was that it was no better than simple statistics; but the statistics were easier to understand and explain.

I realized the machine learning project was a "solution in search of a problem," and left.


Career hack: skip the machine learning and implement the simple statistics, then call it machine learning and refuse to explain it.


statistical regression is also machine learning.


hack v2: call it AI


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