At Kyber, we're building the next-generation document platform for enterprises. Today, our AI-native solution transforms regulatory document workflows, enabling insurance claims organizations to consolidate 80% of their templates, spend 65% less time drafting, and compress overall communication cycle times by 5x. Our vision is for every enterprise to seamlessly leverage AI templates to generate every document.
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At some point I realized the scope was too large. I had spent the most time with msdfgen and hadn’t yet learned enough about the other libraries to write a proper guide. They all worked differently. I kept getting stuck. So I reduced the scope. In redesign 2 I decided to only use msdfgen, but show the various tradeoffs involved (atlas size, antialias width, shader derivatives, smoothing function).