In this presentation given by Tobias Wochinger from RASA and Richard Popa from Orange, find out how Orange is developing AI assistants using the best solutions on the market in collaboration with RASA.

1. Developing Intelligent
Chatbots using RASA
Châtillon, June 13th 2019

2. 2
Context – the BotMan project
Limit dependence on
chatbot providers: simplify
the access to different
solutions
A single entry point allowing
the user to switch from one
chatbot to another and even
chat to a human
Control the UI and give access
to several channels: webchat,
skype, voice, API, …
Take control over the
sensitive data: avoid to push
this data on providers’ cloud
Manage the security of the
access to B2C chatbots in a
single point
Facilitate the chatbots
training

3. 3
Context – the BotMan project
Limit dependence on
chatbot providers: simplify
the access to different
solutions
A single entry point allowing
the user to switch from one
chatbot to another and even
chat to a human
Control the UI and give access
to several channels: webchat,
skype, voice, API, …
Take control over the
sensitive data: avoid to push
this data on providers’ cloud
Manage the security of the
access to B2C chatbots in a
single point
Facilitate the chatbots
training

4. 4
BotMan
Orchestrator Artificial IntelligenceUser Interface
BotMan was developed using 100%
open-source technologies
- Java
- AngularJS
- Redis
- RabbitMQ
- MongoDB
- Docker
- RASA

5. 5
OUR MISSION
AI assistants that work for everyone
We’re building the standard infrastructure layer for conversational AI
that allows all makers to create the best text- and voice-based AI
assistants
Open Source +Community+ Applied
Research

6. 6
Developers across verticals love Rasa: More than 500k downloads and 5,500+
forum members
COMMUNITY
*Cumulative Pypi and Github downloads of Rasa open source tools
Healthcare Insurance Banking
Telecommunications ManufacturingTechnology

7. 7
OPEN SOURCE
● Core: Machine learning-based, contextual decision making
● NLU: Natural language understanding with intent classification and entity
extraction
Rasa: the open source machine learning framework for developers to automate
contextual conversations over text and voice

8. 8
COMMUNITY EDITION
Rasa X: a tool set for developers to build, improve and deploy contextual
assistants with the Rasa Framework
Rasa X Community
A free toolset to build assistants:
View and annotate conversations
Get feedback from testers
Version and manage models
Deploy anywhere
Community Support & Docs

9. 9
Open Innovation with RASA
We built a partnership with RASA based on 3 axis:
– Develop the skills rapidly
– Accelerator for Orange because we have the editor accompanying the projects
– Chatbot audit before going live
– Instant feedback loop
– Quick bug correction
– In less than 48H most of the bug are corrected
– Library mismatch while upgrade to Python 3
– Sharing a “wish-list”
– List of functionalities we would like to have in the product
– Annotating the conversations in the log files
– Important real-life product requirements
WIN WIN
PARTNERSHIP

10. 10
Thank you
Come to see a project demo
during lunch right now!!!