Create intelligent IVR, chatbot, and messaging experiences with intuitive tools built on Nuance speech and AI technologies, APIs, and microservices.
Design, develop and test multilanguage, omni‑channel conversational AI experiences in a single project across voice and digital channels—all with an easy-to-use graphical UI.
Today’s consumers want choice and flexibility: Choice of channels, and flexibility in the way they interact. Mix.dialog lets designers and developers build on a set of predefined dialog nodes that incorporate conversational AI best practices and cover use cases from comprehensive FAQ‑type VAs to highly personalized, transactional bots and IVRs—without having to write a single line of code.
Build conversational AI experiences for voice‑enabled and digital channels in a single project. Optimize the logic for each channel and modality while ensuring consistency and re‑use within a single project. Leverage rich text, media and action buttons in digital channels, and Nuance Vocalizer TTS and prerecorded prompts in voice channels.
Conversational logic built in Mix.dialog builds on context and session awareness. User messages such as “Am I due for a new phone yet?” will be interpreted along with information from prior messages in the same dialog to provide the right answer. Take the dialog understanding further by including external data such as location, account details, and customer preferences to create more personalized experiences.
In Mix.dialog, call flow designers build on core components that can orchestrate mixed‑iniative dialogs. First time users will be guided by the system through conversations step by step, while more experienced users can take the fast track and take control of the conversation.
Bots built with Mix know how to multitask. Users can start a conversation and go down a path for one intent; and when they add a second intent, they can branch out of the current flow to resolve it—and then resume the original task seamlessly.
Mix.dialog lets developers integrate with existing backend systems for authentication, data access, and transaction fulfillment.
Mix.dialog runtime APIs combine Nuance's speech technologies, NLU, and dialog orchestration into a single API—allowing for easier integration with clients including IVR, VAs or bots, smart speakers, mobile apps, and social media engagement channels.
Integrate external systems (such as CRM, customer profile) into your call flow logic to personalize the user experience and better fulfill their needs.
Mix.dialog allows direct integration with RESTful web services and client-side data integration which help create custom client integrations for mobile and web applications that can leverage access to client‑side data and logic.
Define personalized call flow logic and business rules without having to write a single line of code. Build complex, nested conditions via an easy-to-manage, form-filling approach. Leverage data objects with schemas mapping to your back-end methods to minimize data manipulation requirements.
Use built‑in validation and the Try mode to test your dialog logic before pushing it into production. Drive the application logic through all possible paths by simulating different user messages and back-end response data.
The Try mode in Mix.dialog allows developers to test drive the application logic without having to deploy to the target environment. Simulate text and voice modalities and verify system responses, while getting visual feedback on the call flow execution in a protected environment.
While test‑driving application logic through all possible paths in Try mode, simulate backend responses by entering different response data right into the test window.
When configuring call flow logic details, Mix.dialog supports developers by validating the configured dialog nodes and points them at missing content or flawed logic.
Build natural language processing domains and continuously refine and evolve your NLU model based on real‑world usage data. Define user intents (“book a flight”) and entities (“from JFK to LAX next Wednesday”) and provide sample sentences to train the DNN‑based NLU engine.
Train your NLU model with sample phrases to learn to distinguish between dozens or hundreds of different user intents. For each intent, define the entities required to fulfill the customer request. Create custom entities based on word lists and everyday expressions or leverage ready‑made entities for numbers, currency, and date/time that understand the variety of ways customers express that information.
Train the NLU model at any time and test it against practice sentences. Identify problem areas where intents overlap too closely, confidence levels need to be boosted, or additional entities need to be defined.
Deploy the trained NLU model both to the NLU engine and at the same time, as a domain language model, to the speech-to-text transcription engine. This provides the highest accuracy in speech recognition results, semantic parsing, and understanding of user utterances based on your application’s specific language domain.
Use one central view for managing users, access rights, and project versions and deployments. The Mix Dashboard also allows for promotion flows from a sandbox environment to staging and production environments while letting you control multiple data center, multiregional, and hybrid deployment models.
Manage conversational AI projects across your enterprise. Define the supported languages, channels, and modalities on a per-project basis.
Control project versions by integrating with common version management systems. Define deployment packages, and promote them from a sandbox environment to staging and production environments across multiple regions or data centers. Roll back immediately in case of problems with a new version.
Add additional languages or additional channels and modalities to your projects.
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