Mindcase is the infrastructure layer for extracting web data in a structured, usable format. Built for developers and AI teams that need reliable web data without managing scraping infrastructure. Access APIs across popular sources, or get anything across the web built as a custom API for your specific use case.
Six hours in, Mindcase is at #3 Product of the Day with 139 points and 26 comments. Plenty of day left but we're grateful to everyone who upvoted or asked something sharp.
@ashir_murtaza1 That sentence is the whole product in one line, thank you.
The first version takes an afternoon and quietly creates a commitment measured in years, and nobody budgets for the second part because the first part felt so easy.
Every team we have spoken to underestimated the same thing, ourselves included, which is why we ended up building this rather than shipping the thing we originally set out to build.
This is such a great tool and i have been looking for my internal project, would love to see how it works in practical. if you can reveal, how do you handle X platform especially? using official API behind the scenes?
Reliable web data is still one of the biggest bottlenecks for AI applications. Simplifying extraction without teams having to maintain complex scraping setups feels like a valuable infrastructure layer. Great launch!
@better_shab Appreciate that. What surprised us building it is how much of the bottleneck is maintenance rather than the first extraction. Getting data out of a site once is a fun afternoon. Keeping it correct across layout changes, rate limits and anti-bot for a year is the actual job, and that is the part teams underestimate when they decide to keep it in house.
Congrats on the launch! This is a super useful tool and can save so much time for everyone, especially data scientists. Really cool that you support Instagram and TikTok, have been looking for something like this. Will give it a try and let you know what I think!
@isabelzav Appreciate that. For data work the annoying part is usually not getting the data, it is getting it into a table you can actually use without cleaning every column first, which is the bit we spend most of our time on. Tell us what you end up doing with it, we like hearing about the actual use cases.
The infrastructure piece is what makes this interesting. scraping itself is not hard until you need it to keep working.
Mindcase
@ashir_murtaza1 That sentence is the whole product in one line, thank you.
The first version takes an afternoon and quietly creates a commitment measured in years, and nobody budgets for the second part because the first part felt so easy.
Every team we have spoken to underestimated the same thing, ourselves included, which is why we ended up building this rather than shipping the thing we originally set out to build.
Snapventure
Thank you guys. Will give it a shot for scarping TikTok posts of my creators...
Mindcase
Acti
This is such a great tool and i have been looking for my internal project, would love to see how it works in practical. if you can reveal, how do you handle X platform especially? using official API behind the scenes?
BetterClaw
Reliable web data is still one of the biggest bottlenecks for AI applications. Simplifying extraction without teams having to maintain complex scraping setups feels like a valuable infrastructure layer. Great launch!
Mindcase
@better_shab Appreciate that. What surprised us building it is how much of the bottleneck is maintenance rather than the first extraction. Getting data out of a site once is a fun afternoon. Keeping it correct across layout changes, rate limits and anti-bot for a year is the actual job, and that is the part teams underestimate when they decide to keep it in house.
Snipplet
Congrats on the launch! This is a super useful tool and can save so much time for everyone, especially data scientists. Really cool that you support Instagram and TikTok, have been looking for something like this. Will give it a try and let you know what I think!
Mindcase
@isabelzav Appreciate that. For data work the annoying part is usually not getting the data, it is getting it into a table you can actually use without cleaning every column first, which is the bit we spend most of our time on. Tell us what you end up doing with it, we like hearing about the actual use cases.