Retrieval-Augmented Generation (RAG) overview

Retrieval-augmented generation (RAG) lets Optimizely Opal access, understand, and query knowledge sources. By leveraging RAG, Opal can be informed by critical data such as campaigns, content, tests, and more to provide more contextual, accurate, and personalized responses. 

Optimizely Opal RAG

Opal RAG transforms discovery in Optimizely from manual searching into an intelligent, permission-aware, multi-modal retrieval experience, embedded seamlessly in Opal. Making Opal customized and context-aware of your business and organizational assets.

• Unified content graph – Campaigns, tasks, assets, and permissions modeled as nodes or edges. 
• Multi-modal retrieval – Vector + keyword search across text, PDFs, images, video, and metadata.
• Natural language queries – LLM translates user requests into optimized graph queries.
• Permission-aware access – Query-level filters + post-query verification against the Permission Service.
• Intelligent responses – Summaries, lists, and recommendations refined through Opal for contextual insights.

Why RAG matters 

Organizations are rightfully 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• Generate outdated or incorrect content.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 best employees: consulting current documentation, campaigns, and customer data before responding. This is particularly valuable in industries like financial services, healthcare, retail, and enterprise marketing, where accuracy and personalization are critical.

How RAG works

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

Key use cases

• 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

Opal RAG is designed by Optimizely with enterprise-grade security in mind. Your content and campaigns are never exposed to external systems by Opal during the retrieval or generation process.

• 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  – RAG pipelines are operated and monitored internally by Optimizely. You do not need to manage any external connectors.
• Compliance-ready – Designed to meet enterprise security and privacy requirements, including GDPR.

Available RAG sources

Currently, RAG is available for Content Marketing Platform (CMP).