Response Personalization

Personalization of User Responses

Leena AI personalizes user responses based on two main criteria: User Context and User Profile.

User Context

Leena AI enhances user interaction by tailoring responses based on the contextual data or activities associated with the user. This personalization strategy involves:

• Contextual Awareness: Before generating a response, Leena AI considers not only the current query but also the user's historical interaction data or "user memory." This includes past conversations or activities within the system.
• Personalization Mechanism: For instance, if a salesperson has recently added a new lead to the CRM system via Leena AI, with details indicating the prospect is from the manufacturing sector, subsequent interactions are tailored accordingly.

Example Scenario:

When this salesperson asks for case study materials to share with the prospect, Leena AI intelligently recommends only those case studies relevant to the manufacturing industry. This ensures that the information provided is not only relevant but also directly applicable to the user's current tasks or interests.

User Profile

Leena AI also personalizes responses by analyzing various aspects of the user's profile, which includes:

• Profile Data Utilization: Information such as gender, job grade, department, etc., is fetched from an integrated employee master database or central data system.
• Response Customization: When formulating a response to a query, if the answer can be personalized based on this profile data, Leena AI uses a Large Language Model (LLM) to adjust the response to reflect the user's personal attributes.

Summary

By integrating both user context/activity and user profile data, Leena AI provides a highly personalized interaction, enhancing user satisfaction, relevance of information, and overall efficiency in query resolution. This dual approach ensures that each interaction with Leena AI feels uniquely tailored to the individual user, promoting a more intuitive and productive user experience.