The Context Problem: Building AI That Actually Understands Your Business
Learn why context, not the model, decides whether enterprise AI works at scale, and how structure, metadata, and guardrails turn raw documents into context AI can use.
[ Overview ]
What You’ll Learn
- What the context problem is, and why context is a source of competitive advantage now that large language models are largely commoditized
- Why dropping raw PDFs into a bigger context window does not scale, and how structure, metadata, and focus improve accuracy and cost
- The four layers of context: within a document, across related documents, organizational workflows, and the individual user
- How to protect sensitive data with access guardrails, choose the right models for each task, and meet users inside the tools they already work in
“You can take the same ingredients, and a master chef will make it that much better. “
See how to give AI the context it needs.
Hear Jan from Shelf and Sagnik from DocuSign discuss what it takes to move AI from pilot to production: preparing documents, layering context, and keeping sensitive information safe at the scale of hundreds of millions of agreements.
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