Product Recommender
Learn about what the Product Recommender Agent does and when to use it.
The Product Recommender Agent analyzes a customer's unified profile, interactions, relationships, and contributing sources in Reltio to recommend three products with transparent probability scores and evidence-based reasoning.
Who is it for?
Business User
Data Product Owner
Solution Architect
For more information, see About roles.
Why would I use it?
Use the Product Recommender agent to generate accurate, explainable product suggestions based on a customer's behavior, preferences, and context — all mapped to your data model.
When and where would I use it?
Use this agent during digital engagements, support follow-ups, or campaign preparation. It runs in Reltio AgentFlow and leverages the MCP Server to analyze one customer at a time.
How does it support business goals?
It helps improve conversion, retention, and upsell effectiveness by aligning product recommendations with real signals from the customer's data and activity.
Core capabilities
- Analyze unified customer profiles across sources
- Retrieve and evaluate customer interactions
- Incorporate graph-based influence from relationships
- Score candidate products using a weighted model
- Produce explainable, probability-ranked recommendations
- Support filters by product category, interaction window, or ownership
- Respond with detailed data counts and source attribution on request
Watch how it works
Watch how the Product Recommender agent analyzes a customer's profile, interactions, and relationships to generate product suggestions with confidence scores. This short demo shows how the agent surfaces relevant recommendations backed by explainable signals from your unified data model. You'll learn how to review predictions in AgentFlow without modifying customer records.
Safeguards, permissions, and governance
- Recommendations are read-only and do not modify customer or product data
- All scoring and enrichment are based strictly on retrievable and explainable tenant data
- Access to customer records follows existing role-based permissions configured in your tenant
Limitations and edge cases
- Only one customer can be analyzed at a time
- Recommendations depend on the availability of recent interactions and relationships
- Products with missing eligibility or confidence signals may score lower or be excluded