Dialogflow: Google Machine Learning for Chatbots and more
Engaging users in an interactive, personalised and targeted dialog? Get in touch with our experts! This topic is not only high on your priority list, but also of many others. Google’s Dialogflow (formerly API.AI) solution addresses exactly this need. It allows developers to easily and quickly create personal interactions on websites, apps and IoT devices. After integrating the product into their portfolio in September 2016, Google has now announced an Enterprise Edition of Dialogflow. This beta release adds a number of important features to the product:
- Google Cloud Platform Terms of Service: Dialogflow Enterprise Edition is covered by the Google Cloud Platform Terms of Service, including the Data Privacy and Security Terms. Enterprise Edition users are also eligible for Cloud Support packages, and the Enterprise Edition will soon provide SLAs with committed availability levels.
- Flexibility and scale: Dialogflow Enterprise Edition offers higher default quotas so it’s easier to scale your app up or down based on user demand.
- Unlimited pay-as-you-go voice support: While both the standard and enterprise editions now allow your conversational app to detect voice commands or respond to voice conversations, Dialogflow Enterprise Edition offers unlimited pay-as-you-go voice support.
Especially the adoption of the general Google Cloud Platform Terms of Service, which include GDPR compliance (EU General Data Protection Regulation), will be good news for all those customers who are sensitive to data privacy concerns.
If you’ve never heard of Dialogflow before, here is what it offers:
- Conversational interaction powered by machine learning: Dialogflow uses natural language processing to build conversational experiences faster and iterate more quickly. Based on a few examples of what users might say, Dialogflow builds a unique model that learns what actions to trigger and what data to extract so from the customers message. This information is used in turn to build a precise and meaningful conversation path. Moreover, using Dialogflow’s integrated history view, you can give the system feedback on how it handled past conversations and help it learn from them for the future.
- Build once and deploy everywhere: Dialogflow conversation flows are built once and can be deployed anywhere: on your website, on your app or on 32 different platforms, including Google Assistant, Amazon Alexa, Microsoft Cortana, Facebook Messenger, Slack, Twitter, and other popular messaging services. Dialogflow also supports multiple languages and multilingual experiences so you can reach users around the world.
- Advanced fulfillment options: Fulfillment defines the corresponding action in response to whatever a user says, such as processing a request to reset a password, ask for the weather forecast or order a pizza. Dialogflow allows you to connect to any webhook for fulfillment whether it’s hosted in the public cloud or on-premises. Dialogflow’s integrated code editor allows you to code, test and implement these actions directly within Dialogflow’s console.
- Voice control with speech recognition: Dialogflow enables your conversational app to respond not only to read and write, but to also conduct entire voice conversations. It’s available within a single API call, combining speech recognition with natural language understanding.
Whether chatbot, intelligent agent, robo advisor, interactive support system – Dialogflow allows you to build a scalable, integrated solution very fast and friendly (not furious).
More information on the Dialogflow enterprise edition.