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Optimizing AI Inputs on the Web: Raidu's Readability Engine Built with Intel® Liftoff

Eugenie Wirz, Intel Liftoff for Startups

Intel features Raidu's innovative engine that evaluates and optimizes web content for machine readability

We’re thrilled to be featured in Intel’s Tech Innovation blog, highlighting our groundbreaking work in optimizing web content for AI consumption.

Key Highlights from the Article

Intel’s Eugenie Wirz explores how Raidu is revolutionizing the way AI models interpret web content through our innovative Readability Engine. The article emphasizes our core philosophy:

“AI won’t get smarter until the web gets cleaner.”

Our Innovation: The LLM Readability Engine

The article details our comprehensive engine that includes:

  • Token Efficiency Analyzer - Optimizes content to reduce token usage while maintaining meaning
  • Semantic Scanner - Identifies and preserves important semantic structures
  • Context Scorer - Evaluates content relevance and context quality
  • HTML Cleaner - Removes noise and improves content structure

The Problem We’re Solving

As highlighted in the Intel article, the web wasn’t designed for machines. Our founder, Shiva Ganesh Bellamkonda, identified that AI models struggle with:

  • Excessive noise in web content
  • Poor semantic structure
  • Inefficient token usage
  • Context loss in content extraction

Beyond Readability: AI Governance

The article also mentions our expansion into AI governance, where we’re building tools to:

  • Monitor AI usage across devices
  • Secure enterprise AI implementations
  • Ensure compliance and safety
  • Prevent unauthorized AI access

Intel Liftoff Partnership

Through the Intel Liftoff startup program, we’ve been able to accelerate our development and bring innovative solutions to market faster. The program has provided invaluable resources and expertise to help us scale our technology.


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