Tools
Extend your Agent step's capabilities with specialized tools for accurate task execution.
Overview
Tools are specialized capabilities you can attach to AI Agent steps. They allow the agent to perform specific tasks with higher accuracy than relying solely on LLM prompting. Tools are particularly useful for classification, data extraction, and other structured tasks.
Why Use Tools?
Higher Accuracy
Pre-trained models are fine-tuned for specific tasks, providing more consistent and accurate results than general LLM prompting.
Token Savings
Tools handle specific tasks efficiently without consuming LLM tokens for classification or extraction logic.
Available Tools
This tool is trained and fine-tuned using distilbert-base-uncased, a lightweight but powerful transformer model. It accurately classifies user queries into predefined intent categories.
Supported Intents
Requirement Submission
User is submitting a project requirement or RFP
General Query
General questions about services or company
Contact Details
User is asking for contact information
Feedback Submission
User is providing feedback about services
Appreciation
User is expressing thanks or positive sentiment
Greeting
User is saying hello or starting conversation
Job Application Submission
User is inquiring about jobs or submitting an application
Use Case: Mixed Inquiry Routing
IT service companies often receive both client inquiries and job applications through the same channels. This tool helps automatically separate them with 95% accuracy, ensuring leads go to sales and applications go to HR.
How to Attach a Tool
- Open your chatbot and select an AI Agent
- Navigate to the Tools section in the step configuration
- Click Add Tool and select from available tools
- Configure any tool-specific settings if required
- Save your changes
Once attached, the agent will automatically use the tool when processing relevant queries. You can reference the tool's output in Condition steps to route conversations based on the classified intent.
LLM vs Tool Classification
| Aspect | LLM Prompting | Intent Classifier Tool |
|---|---|---|
| Accuracy | Variable, can hallucinate | Consistent, ~95% accuracy |
| Token Usage | Consumes LLM tokens | No LLM tokens used |
| Speed | Depends on LLM response time | Fast, dedicated model |
| Flexibility | Any classification task | Pre-defined intents |
Coming Soon
Custom Intent Classifiers
We're working on the ability to train custom intent classifiers for your specific use cases. Define your own intents and train models on your data.
Next Steps
Branch
Route conversations based on tool outputs