3 ● End-to-end development suite for building conversational UI. ● Previously known as API.AI ● Sept 2016, acquired by Google ● Powered by Machine Learning Dialogflow
4 Why Dialogflow ● Powered by Machine Learning (NLP) ● Scalable: separate your conversation text from code ● Build faster with the Web UI ● Advanced fulfillment options and multi channel integrations ● Analytics ● Speech / Voice Integration ● Multi-lingual bot support (20+ languages) ● Part of Google Cloud (60+ cloud services) Intent Recognition (NLP) ... Web Console Powerful SDK Supervised Training Cross-platfor m
5 What’s new? ● Soon Dutch Assistant in the Netherlands! ● Six new voices ○ Including John Legend ○ Voices were created through Wavenet ● Smart Displays: Support for AoG table cards ● Dialogflow History Support ● Diagnostic Info ● Train Negative Fallback examples ● Dialogflow Enterprise in GA!
9 Part of Google Cloud also means: ● Easy integration /setup with 60+ products & services. ● Stay in the cloud. Improve latency & security. Other advantages User types in Web Interface Machine Learning Detection Call to Dialogflow Store in Data Warehouse Webhooks Return to customer vs.
10 Part of Google Cloud also means: ● Easy integration /setup with 60+ products & services. ● Stay in the cloud. Improve latency & security. ● Logging, Tracing, Debugging, Error reporting Other advantages
11 Part of Google Cloud also means: ● Easy integration /setup with 60+ products & services. ● Stay in the cloud. Improve latency & security. ● Logging, Tracing,Debugging, Error reporting ● User Roles, Permissions Other advantages
12 Part of Google Cloud also means: ● Easy integration /setup with 60+ products & services. ● Stay in the cloud. Improve latency & security. ● Logging, Tracing,Debugging, Error reporting ● User Roles, Permissions ● Compliant Other advantages
13 Part of Google Cloud also means: ● Easy integration /setup with 60+ products & services. ● Stay in the cloud. Improve latency & security. ● Logging, Tracing,Debugging, Error reporting ● User Roles, Permissions ● Compliant ● Scalable, No Ops Other advantages
Confidential + Proprietary Human take-over chatflow with sentiment detection Your users type into a chat UI which can be integrated in your apps, websites or social media channels. When user ask to talk with a human, the operator can take over from the chatbot. Detect in real-time the users mood, and let the operator take over from the chatbot. This solution uses Kubernetes containers with Socket.io to enable realtime, bi-directional communication between web clients and servers. Architecture: Dialogflow with human handoff User types in chat UI Chatbot or User replies Operator Dashboard Kubernetes Engine Container Registry Customer Client Kubernetes Engine Back-end Kubernetes Engine Back-end Kubernetes Engine NLP API ML call for sentiment detection Pass user utterance to chatbot Return text response to user User asks to talk with human Negative sentiment let a human take over the conversation Operator types in chat UI User replies Containers images can be stored in the Container Registry Dialogflow Enterprise
21 ● Custom implementation (Pub/Sub and BigQuery) ● Learn which questions has been asked the most ● Improve your bot over time ● Track user experience Chatbot User Analytics
37 I’ve built this demo on my own in a couple of evenings. Improve your user experience with a little more cloud. ● Fast & Easy integration of various cloud products: ○ Kubernetes Engine, Cloud Builder, Container Registry ○ Cloud Functions, Pub/Sub, BigQuery ○ DLP API, NLP API ● Cloud IAM, Logs, Traces, Debugging, Error reporting out of the box ● Scalable & Complaint: Ready to go live. Conclusion
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