🔍 Retrieval-Augmented Generation (RAG) in Sen AI Studio

Sen AI Studio supports Retrieval-Augmented Generation (RAG) to enrich LLMs with real-time, governed data. Embedded within our orchestrated AI framework, it ensures trust, compliance, and scalability.

Boss Catalog: The Metadata Backbone

Acting as the central metadata authority, Boss Catalog powers every interaction—data, applications, LLMs, workflows—across the platform. It enforces governance and enables context-aware orchestration.

Data Governance

• Lineage & Provenance: Tracks every dataset, transformation, and prompt input.
• Access Control: Fine-grained, role-based access to all assets.
• Data Quality & Classification: Auto-tags sensitive data (PII/PHI) and monitors data quality.

AI Governance

• Prompt Traceability: Prompts are versioned and metadata-linked.
• Model Usage Audit: Tracks LLM use per user and task.
• Bias & Drift Monitoring: Ensures fairness and performance over time.
• Guardrails & Policy Enforcement: Enforces ethics and explainability.

Metadata Governance

• Single Source of Truth: Boss Catalog governs apps, dashboards, and RAG prompts.
• Schema & Context Governance: Validates and tracks dynamic RAG inputs.

Workflow Governance

• Approval Chains & Event Tracking: All actions are logged and auditable.
• Versioned Workflows & Templates: Enables rollback and safe iteration.

Access & Compliance

• SSO, MFA, Role Management: Enterprise-grade access with full audit trails.
• Compliance Ready: Supports HIPAA, GDPR, SOC2 through structured policies.

RAG Enablement in Action

With Boss Catalog, Sen AI Studio dynamically constructs context payloads—such as dataset samples, schema definitions, and metadata—for each LLM prompt. This results in:

• Real-time relevance
• Structured augmentation
• Governed LLM orchestration
• Fully auditable and explainable workflows