The AI Data Layer
Powering Superior AI Outcomes
Shelf transforms enterprise documents, files, and knowledge into structured, contextualized and governed information that AI can retrieve, interpret, and use reliably.
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Your data is the difference between AI that fails and AI that scales.
Data Access ≠ Data Understanding
AI can access enterprise information without understanding how your business works. Retrieval may find relevant content, but without the right structure, relationships, and business context, AI cannot consistently determine what information means, how it connects, or when it applies.
Teams compensate with prompt tuning, manual tagging, data pipelines, and application-specific logic. That adds engineering and maintenance to every new use case while the underlying problem remains.
The result is inconsistent answers, limited automation, and AI initiatives that fail to scale across the enterprise.
At best, each workaround addresses part of the problem, but none creates a reusable data foundation that can support AI across use cases and at scale.
Transform enterprise knowledge into an intelligent, continuously improving AI-ready data layer.
Shelf Cortex transforms enterprise documents, files, and knowledge into a reusable data foundation for the AI systems above it.
It adds the structure AI needs to retrieve and connect information, the business context needed to interpret it correctly, the governance required to control how it is used, and continuous quality assurance as the underlying knowledge changes.
How the AI Data Layer Works
Translate + Structure
Optimize enterprise information for AI use. Turn documents, files, and other knowledge sources into machine-usable structures, metadata, and relationships that make information easier to retrieve, connect, and interpret.
Add Business Context
Give AI the meaning specific to your company. Enrich information with context around products, policies, terminology, markets, processes, relationships, audiences, and operating rules so AI can understand what information means and when it applies.
Govern
Carry enterprise controls into AI. Apply permissions, access rules, ownership, review, publishing, and lifecycle controls as information is reused across applications and AI experiences.
Continuously Quality-Assure
Keep the information behind AI current. Continuously identify outdated, duplicate, conflicting, incomplete, and low-quality information as enterprise knowledge changes.
Turn enterprise data into a foundation for accurate and scalable AI.
Give AI business context it can reuse
Model company-specific terminology, relationships, policies, and operating rules once, then make that context available across multiple AI experiences.
Automated quality assurance and continuous improvement
Move recurring structure, enrichment, governance, and quality work into a shared layer instead of rebuilding it around each application.
Drastically improve AI retrieval and interpretation
Give AI more than relevant text by adding the structure and context needed to connect information and apply it to the right situation.
Scale without separating AI from enterprise controls
Reuse knowledge across applications while preserving permissions, ownership, access rules, and governance requirements.
Build once, use for any AI use case
Continuously assess the information AI depends on as documents, policies, products, and business rules change.
Security, governance, and reliability
Cortex preserves permissions, access rules, ownership, and governance across connected knowledge sources and the AI systems that use them.
It supports enterprise security and compliance requirements with established certifications, security controls, and auditable access.
APIs and SDKs make governed knowledge available across your existing applications and infrastructure without requiring you to move or duplicate source content.
Security, availability and confidentiality trust
EU-compliant data protection protocols
Application security & governance framework
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