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We're at a pivotal moment in AI's evolution.

While compute power grows exponentially, we're still operating on static, unstructured data from "one internet." The foundation models are built, but they're trapped in a world of fossil fuel data - stripped of context, attribution, and relationships. The next wave of AI needs dynamic, living context systems.

Today's AI Stack is Built on Static Data.

1. Foundation models trained on stripped, unattributed internet data can't maintain continuous context
2. Professional knowledge requires trust and verification - you need to know where information comes from and how it evolves
3. Major AI companies are building closed systems that treat knowledge as a static resource rather than a living, collaborative asset

As a result, AI applications remain unreliable for professional work. They can't maintain continuous context across sources, can't verify their claims, and can't enable true collaboration. Organizations either trust unverified outputs or spend millions building custom solutions.

Introducing Dynamic Context Delivery Systems.

The New Fuel for AI What if we could make every AI system context-aware? What if professional knowledge could be structured, verified, and attributed while maintaining living relationships across sources? We're building that future - where data isn't fossil fuel, but a renewable resource that grows with every interaction.

Inspired by GitHub's impact on code collaboration, we are building a universal context layer that transforms professional content into verified, AI-ready datasets while preserving attribution and relationships.

Our Artifacts:

• Waffly Corp: Universal dataset managment system for dynamic knowledge extraction and access control [website]
• Platogram: Open-source backend for large-scale RAG systems [github]
• Shrinked: Consumer application proving the power of continuous context [try it]

Join us in building the collaborative, attributed future of AI.
[email protected]