Handle Multiple Intents Using Rasa NLU TensorFlow Pipeline

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Platform Overview

Rasa extends LLMs with structured flows, deterministic logic, and built-in recovery patterns.

CALM

CALM extends the flexibility of LLMs with the reliability of deterministic logic.

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Manage layered, real-world conversations with memory, logic, and adaptability built in.

Enterprise RAG

Retrieve information in real time, so every answer is fresh, verifiable, and aligned with your trusted data.

NLU

Begin with intent-based structure, expand with AI flexibility as needed.

Voice

Real-time voice infrastructure with enterprise-grade speed.

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Create agents that take initiative and adapt to complexity.

Multilingual AI

Expand globally with agents that adapt to language, tone, and context.

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Coordinate agents and tools to give users the right help at the right moment.

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MCP gives your AI agents a standard way to connect with APIs as tools.

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Resolve routine issues quickly with automation, and make room for deeper support work.

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Automate processes, orchestrate systems, and free teams to focus on growth.

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Finance & Banking

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Retail

Guide shoppers, resolve issues, and boost conversions across every channel.

Government & Public Sector

Handle high-volume inquiries and streamline workflows without compromising trust.

Insurance

Automate policy and claim interactions with precision and transparency.

Healthcare

Automate complex conversations securely for better patient and provider outcomes.

Telecom

Handle high-volume support with agents that connect systems and recover from errors.

Travel, Transport, & Hospitality

Automate tasks from booking to boarding and resolve issues quickly.

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Handle Multiple Intents Using Rasa NLU TensorFlow Pipeline

Posted Jun 11, 2018

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Handle Multiple Intents Using Rasa NLU TensorFlow Pipeline

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Building A Conversational AI Agent for Sourcing Motorcycles with RASA

Building an AI Agent for a Dental Clinic with Rasa

AI that adapts to your business, not the other way around

Build your next AI

agent with Rasa