If your AI can’t tell the difference between an approved contract and an archived rough draft, it isn’t business-ready. Most generative AI rollouts get stuck not because the models are bad, but because they are blind to your business: they don't know who is involved in or who might have left the project, which project a file belongs to, or who has permission to see it.
Standard retrieval-augmented generation (RAG) forces models to guess those connections from scratch on every single prompt. That burns expensive compute, returns half-baked answers, and risks exposing sensitive data to the wrong people. To get accurate, trusted answers, AI doesn't just need access to documents—it needs a governed Context Layer.
Join us on Dec 10 at 10:00 AM PT / 1:00 PM ET for a look at how teams are fixing the context problem to build AI people can trust.
You’ll learn:
- Why Context Matters: Why basic search and out-of-the-box RAG break down at scale, and the hidden costs of letting models guess how your data fits together.
- Inside the Context Layer: How to automatically inject permissions, project histories, and metadata into every prompt—without making teams manually tag files.
- Governing AI agents: Practical ways to tune business context for custom workflows while ensuring confidential data stays locked down, whether you're using Microsoft 365 Copilot, OpenAI, or internal LLMs.
Register Now
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ADDITIONAL RESOURCES
Unify, Protect, and Control Project Documents
A guide to improving visibility and productivity throughout a project's lifecycle.
Unify, Protect, and Control Project Documents
A guide to improving visibility and productivity throughout a project's lifecycle.
Unify, Protect, and Control Project Documents
A guide to improving visibility and productivity throughout a project's lifecycle.