A team has developed an open-source AI methodology for scoring tokenization cases, built through 150,000+ hours of analysis of securities frameworks, prospectuses, and exemptions across major financial centers since 2018; this transparent methodology allows anyone with a GitHub account to fork and apply it to their own projects, though it is not a rating agency and does not involve human scoring.
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Tokenization: Open-Source AI ScoringAjouté :
And we have spent more than if I'll tell you more than 150,000 hours cumulatively on uh analysis of starting from 2018. This is one of our key metrics. We spent a lot of time, a lot of hours as a team to um analyze securities frameworks, offerings frameworks, prospectuses, exemptions throughout the world uh within the certain financial centers.
And we have built our methodology that actually allows uh AI uh artificial intelligence to score the case.
Um and that's is open source. I will show you again.
And something that anyone can apply.
And uh it's now on its first better version better uh stage. So, any business uh and by by the way, the RWA screeners what I'm going to show you are having every asset have a score.
Um ABC something like Moody's. I want to emphasize here we're not a scoring agency. We don't have any license to do scoring. This is why none of the score is being done by humans. Um this is a absolute transparent methodology that we commit to. Anyone in the world that has a GitHub and a bit of knowledge can fork this and apply it to their projects, to their issues
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