Retrieval-Augmented Generation (RAG) overview

Retrieval-augmented generation (RAG) gives Optimizely Opal access to your data, campaigns, content, and tests. Opal uses this data to generate contextual, accurate, and personalized responses.

Why RAG matters

Organizations are cautious about AI. Without checks, AI can do the following:

• Generate outdated or incorrect content.
• Produce tone-deaf or off-brand messaging.
• Violate compliance or privacy requirements.

RAG changes this dynamic by helping AI act more like your employees: consulting current documentation, campaigns, and customer data before responding. RAG is especially valuable in financial services, healthcare, retail, and enterprise marketing. These industries require accurate, personalized AI content.

How RAG works

RAG retrieves and processes data through three steps before Opal generates a response.

1. Retrieval – The AI searches a vector database to find the most relevant information across structured and unstructured sources.
2. Processing – Opal analyzes the retrieved data and adds context for accuracy.
3. Generation – Using that context, the AI generates an accurate, brand-consistent response.

Opal RAG features

Opal RAG replaces manual searching with a permission-aware retrieval experience embedded in Opal. RAG gives Opal context about your business data and assets.

• Unified content graph – Campaigns, tasks, assets, and permissions modeled as nodes or edges.
• Multi-modal retrieval – Vector and keyword search across text, PDFs, images, video, and metadata.
• Natural language queries – A large language model (LLM) translates user requests into optimized graph queries.
• Intelligent responses – Summaries, lists, and recommendations refined through Opal for contextual insights.

Use cases

The following examples show how different roles use RAG in Opal:

• Marketers – Show me all assets tagged with 'Holiday Promotion' used in live campaigns.
• Campaign managers – What tasks and approvals are pending for the Black Friday campaign?
• Developers – List all stale feature flags not updated in 90 days.

Data privacy and security

Optimizely designed Opal RAG to meet enterprise security requirements. Opal never exposes your content and campaigns to external systems during retrieval or generation.

• Internal-only data processing – All data retrieval, embeddings, and indexing happen within Optimizely's secure infrastructure.
• Permission-aware access – Every query respects user roles and permissions, ensuring you only see content you are authorized to access.
• Managed data sync – Optimizely operates and monitors RAG pipelines internally.
• Compliance-ready – Meets enterprise security and privacy requirements, including General Data Protection Regulation (GDPR).

Available RAG source

RAG is available for Content Marketing Platform (CMP).