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Integrate with CRMs and other backend systems

Connect with existing services and fetch data from any internal or external API using custom actions.

Customizable NLU

Easily integrate custom components like sentiment analysis with Rasa’s modular NLU pipeline. Power text or voice-based interfaces.

Seamlessly hand off customers to human agents

Smoothly transfer to an available agent when customer requests go outside of an AI chatbot’s domain.

Customer experience for the modern era, made possible through conversational AI

The bar has been raised on customer experience, and today's companies are looking beyond the call centers of the past. Customers increasingly prefer self-service options and on-demand support that lets them get help whenever they want, wherever they want. Meanwhile, companies across industries are finding new ways to reduce the costs of one-on-one conversations with customers while setting themselves apart from the competition through digital innovation.

Chatbots, voice assistants, and automated IVR systems represent the new wave of customer experience. Conversational AI is increasing in sophistication, allowing companies to automate the types of conversations that wouldn’t have been possible five years ago. Rasa allows companies to go beyond simple FAQ bots to create transactional, contextual conversation flows—the types of automated conversations that really help users.

Deflect contacts so agents can focus on the important problems

Empathy, creativity, complex problem solving. Free up human agents to do what they do best. Out of the thousands of contacts support agents handle each day, many are repetitive, simple requests. When these repetitive call drivers are directed to human support reps, they clog queues, causing long wait times, leading to frustrated customers. These contacts have a negative effect on operations as well, affecting SLAs and cost per call.

Chatbots and voice assistants offer an effective front line of support to deflect the types of simple questions that come up again and again. Login issues, frequently asked questions, troubleshooting, and call routing take time away from human agents and drive up the costs of support.

Companies using Rasa have seen substantial increase in containment rates after implementing conversational AI assistants for customer service. This strategy allows companies to scale operations while keeping costs under control, fueling growth to new markets.

N26, a fast-growing bank, made customer service automation a key part of its expansion strategy. Using Rasa, N26 built a network of digital assistants accessible through the company’s app, which support customers in 5 languages and regions. This allowed N26 to achieve a 30% call deflection rate, a success metric that allowed N26 to grow operations with maximum efficiency.

Rasa powers customer experience on multiple channels

Today's customers now reach out to brands across a huge digital surface area—social, mobile, web, and voice-enabled devices—and they expect the experience to be seamless. Rasa assistants easily connect to multiple channels, with a single assistant running the backend experience. The assistant’s responses can be customized on a channel-specific basis, allowing enterprises to serve targeted content to different audiences.

Rasa offers 10 built in messaging channels, including popular platforms like Facebook Messenger, SMS, and WhatsApp. A flexible architecture allows development teams to build custom messaging channel connectors.

Provide customers with localized support

Expand to new regional markets with multi-lingual customer service. The traditional way of offering multi-lingual support involves maintaining support centers in multiple geographies, an expensive proposition that's nearly impossible to scale. Automating multi-lingual support offers an effective alternative, allowing customers to get the help they need in their preferred language, while conserving resources.

Rasa works with any language, even regional dialects. Rasa’s unmatched customization ability and flexible machine learning pipeline mean that you can build multilingual customer service chatbots to support your customers around the world.

Deflect contacts by providing automated first-line technical support.

  • Troubleshoot internet, cable, or phone connections
  • Set up a new device
  • Request a replacement device
  • Install software
Case Study

Create a new sales channel through an AI assistant built with Rasa

The Challenge

ERGO, a leading European insurance company, wanted to expand their customer service operations to provide 24/7 coverage—all while reducing costs.

Basic chatbots and IVR systems have been rejected by users for being frustrating and unhelpful. Current mass-market solutions are limited to basic, FAQ-based bots that are unable to handle complex requests and have no connection to back-end systems. Given ERGO’s award-winning chat agents and concerns about data security, none of these solutions worked for them.

The Solution

ERGO deployed Rasa Open Source and Rasa Enterprise, laying the framework to automate over 30% of customer requests before continuing to full automation. The ERGO team identified which skills to prioritize through an extensive analysis of thousands of real customer service conversations. A 12-week training phase with agents further improved the accuracy of the system. The AI immediately suggests suitable answers, dramatically reducing response time and boosting productivity and resource availability.

The Results

The deployment convinced top management to invest in making the AI assistant fully autonomous for selected use cases. In addition, the company wants to deeply integrate the assistant into their live chat system.

Rasa Blog

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