You don't need to read another post-mortem to understand why enterprise AI projects fail. The organizations that have moved their AI from pilot to production understand that AI requires context. 

The knowledge layer enables AI to understand how individual facts relate to one another, what has changed, and what has been previously decided. A model trained on siloed data sees disconnected records rather than relationships, so it can’t reason without sufficient context. By acting as glue, the knowledge layer connects GenAI and agentic systems to accessible, organized data. 

On July 21, we’ll discuss why the knowledge layer is the missing ingredient your enterprise AI needs. Discover what your organization can gain from implementing a knowledge layer, including the ability to:

• Trust every AI answer, back to your source data
• Prove every AI decision with a complete audit trail
• Synthesize intelligence across disparate data systems and teams
• Make use of your existing data investments instead of replacing them