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December 4, 2025 26 mins

Raviteja Yelamanchili shares how Scale AI transformed banking cycles from one year to real-time and why your most valuable enterprise data isn't being collected.

Topics Include:

  • Scale evolved from data annotations company to enterprise AI solutions provider
  • Healthcare system transformed patient transcriptions into value using reinforcement learning research
  • Blank slate customer problems allow Scale to experiment with latest methods
  • Many customers propose solutions before explaining their actual underlying business problems
  • Biggest AI misconception: technology will replace jobs rather than augment productivity
  • Don't wait for perfect AI—start learning through iteration and evolution now
  • Banking credit cycle transformed from one-year process to real-time strategic insights
  • Scale deploys flexibly across EC2, EKS, or Bedrock based on customer requirements
  • Enterprises want business value generation more than academic research papers alone
  • Next 12-24 months focus: making data consumable and leveraging unused datasets
  • Tribal knowledge from experienced SMEs represents most valuable yet uncollected data
  • Agent-based learning captures expertise through feedback loops on Scale's SGP platform


Participants:


See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

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