Core Dataplane Services

Shared services that make AI permission-aware and production-ready

Beyond integration execution, the Dataplane provides core services that ensure data is contextual, governed, and suitable for AI consumption.

Enterprise Metadata Model

All data entering the Dataplane is normalized into a structured metadata model:

• Business-aligned dimensions
• Typed attributes
• Lineage and provenance tracking

Access emerges from metadata structure. If data does not belong to a user context, it does not appear in results.

Permission-Aware Retrieval (RAG)

Retrieval services enforce identity and metadata filtering before data reaches AI.

Capabilities include:

• Identity-scoped queries
• Mandatory metadata filters
• ABAC evaluation
• Deterministic result scoping

AI never receives raw, unfiltered system payloads.

Vector Search with Metadata Filtering

Vector similarity search operates together with enforced metadata constraints:

• Similarity ranking
• Identity-derived filtering
• Dimension-based scoping

This prevents semantic leakage across permission boundaries.

Delta Sync and Change Data Capture (CDC)

The Dataplane supports structured synchronization patterns:

• Full synchronization
• Incremental updates
• Content-based change detection

This ensures predictable refresh cycles and efficient updates.

Structured and Unstructured Ingestion

Supported ingestion types include:

• Structured business records (CRM, ERP)
• Document storage systems
• Hybrid datasets

All ingestion converges into the same metadata and governance model.

Secure Runtime and Network Egress Control

Execution is governed by:

• Azure networking controls
• Environment isolation
• Explicit egress policies
• Fail-closed enforcement behavior

No outbound access is permitted unless explicitly allowed by policy.

These services collectively ensure that enterprise data becomes AI-ready without compromising identity, governance, or auditability.