Intent-Based Skill Classification

Luma now supports Semantic skills. These are Intent-Based Skills that use AI-powered classification to define how a skill is recognized and invoked. These skills are built using structured intent parameters called Classification Details. These components are generated through a guided skill creation workflow, where Luma prompts the user for information and automatically constructs the classification logic. This approach eliminates the need for training data, reduces effort, and enhances skill consistency. Additionally, you can now publish the skills individually or bulk publish the classifications.

For more information, refer to  Intent-Based-Skills-(Semantic-Skills)

Conflicting skill identification 

Luma can now detect potential conflicts between newly created skills and existing ones. This AI-based conflict ensures a clean, unambiguous, and well-structured skill repository. Skills with overlapping or similar purposes introduce execution errors and increased support overhead. Luma can now highlight the Reason for the conflict and provides Suggested Actions that the skill developer can act upon.

For more information, refer to Creating a new skill → Conflict-Check

Semantic Skill Search

No need to train Luma to identify skills. Luma now uses the power of AI to determine the most appropriate skill to invoke. Rather than depending on a fixed list of phrases or keywords, these skills use Classification Details to identify skill's intent based on natural language. This method is flexible and adaptive to variations in how users phrase their requests, making it ideal for scaling Luma functionality in environments with dynamic or complex needs.

For more information, refer to Invoking a Skill

Natural Language Entity Recognition (NER)

Skip manually tagging attributes in phrases and let Luma automatically identify and populate the required information from the conversation flow. Luma uses AI to automatically populates all the attributes that are part of the skill (as user prompts) and the predefined tenant-level Generic Entities. This intelligent entity recognition significantly reduces the manual effort required during skill development, accelerates go-live time, and improves the user experience by allowing Luma to gather more context from every user interaction.

For more information, refer to Invoking a Skill → Entity-Extraction-and-Attribute-Handling