Intent

What is an Intent in Sub Agent?

An Intent represents a specific goal or action that an AI sub-agent in UPTIQ is designed to handle based on user input. It helps the reasoning engine understand and classify user queries to trigger the appropriate response or workflow.

Key Components of an Intent:

1. Intent Name

   • A unique identifier for the intent.

   • Should be easy to distinguish from other intents within the same sub-agent.

2. Intent Description

   • A clear and comprehensive explanation of the intent’s purpose.

   • Used by the UPTIQ reasoning engine to match user queries accurately.

   • Should be detailed yet simple for optimal LLM processing.

3. Intent Examples

   • Up to five sample queries that help the reasoning engine learn how users may phrase their requests.

   • These examples improve intent recognition accuracy.

How Intent Execution Works in UPTIQ AI Sub-Agents

When a user query is triggered, UPTIQ's reasoning engine follows a structured process to identify and execute the appropriate intent. Here's how it works:

1. User Query Processing

• The AI receives the user's input (e.g., "What is the total liability value?").

• The reasoning engine analyzes the query and compares it with defined intent examples to determine the best match.

2. Intent Matching

• If the query closely aligns with an existing intent's name, description, or examples, the system selects that intent.

• If no exact match is found, the engine attempts to generalize the query to the closest related intent.

3. Workflow Execution

• Once an intent is matched, the system automatically triggers the associated workflow.

• The workflow defines the next steps, such as:

  • Fetching relevant information from connected documents or databases.

  • Performing calculations or data extractions.

  • Formatting and returning the response to the user.

4. Response Generation

• The AI processes the workflow output and delivers a structured response to the user.

• The response is formulated based on the data retrieved and may include text, summaries, or extracted document details.

5. Continuous Learning & Improvement

• If users frequently ask queries that don’t match existing intents, developers can refine intents by:

  • Adding new examples to improve recognition.

  • Modifying intent descriptions for better clarity.

  • Creating new intents for uncovered scenarios.

Key takeaways for developers

✅ Purpose-Driven Design – Intents represent specific user goals or actions, enabling AI agents to deliver accurate and contextually relevant responses.

✅ Clear Naming for Easy Identification – Use unique, descriptive names to distinguish intents within sub-agents, improving clarity and organization in workflows.

✅ Comprehensive Descriptions – Provide clear, unambiguous descriptions to help the UPTIQ reasoning engine match user queries effectively.

✅ Use Examples for Precision – Add up to five examples of user queries to guide the reasoning engine and improve accuracy in intent recognition.

✅ Workflow Integration – Each intent is automatically linked to a workflow stub, allowing developers to define precise actions when an intent is matched.

✅ Iterative Refinement – Regularly update intent examples and descriptions to handle evolving user queries and improve performance over time.

✅ Modular Scalability – Intents can be expanded and refined without disrupting the functionality of other intents or workflows, ensuring scalability and flexibility.

By designing and maintaining well-structured intents, developers can create intelligent, responsive, and user-centric AI agents within UPTIQ.

How to create an intent in Sub Agent?