1. Applying Conversational AI
in the Enterprise
Rasa Summit 2021

2. Rasa has traction across industries with over 10 million downloads worldwide.
*Cumulative Pypi and Github downloads of Rasa open source tools
Healthcare Insurance Banking
Telecommunications Manufacturing
Retail & Technology
*Cumulative Pypi and Github downloads of Rasa open source tools
m
m
m
m
Downloads

3. Natural language interfaces allow customers to get things done on their terms
A seamless customer experience

4. You might run into these challenges when applying conversational AI in the
enterprise
Meet security standards
Integration with third-party services
Varying DevOps expertise
Scaling conversations while providing seamless user experience

5. AI assistants need to meet security standards in an enterprise setting
ENTERPRISE CHALLENGES

6. AI assistants need to meet security standards in an enterprise setting
ENTERPRISE CHALLENGES
● Secure storage for credentials, environment variables, and other details
● Data privacy - data in motion and data at rest
● Access controls

7. As they scale, they’ll need to be integrated with third-party services
ENTERPRISE CHALLENGES

8. As they scale, they’ll need to be integrated with third-party services
ENTERPRISE CHALLENGES
● Use a data-driven approach to come up with an integration plan
● Follow the Single Responsibility Principle when you create custom actions

9. Good DevOps practices are critical
ENTERPRISE CHALLENGES

10. Conversations will need to scale too
ENTERPRISE CHALLENGES

11. But a great customer experience should be a governing factor
ENTERPRISE CHALLENGES

12. Mady Mantha
Senior Technical Evangelist
m.mantha@rasa.com
@madymantha
Get in touch

13. … and so many other dimensions of enterprise scale
Quality
Assurance More
natural
languages
Larger
teams
Approval
processes Increased
traffic
Deployments
...

14. DRAFT SLIDES

15. Applying conversational AI in the enterprise
Who is the audience for this talk?
● Conversational teams in enterprises familiar with Rasa
How should they feel after watching it?
● Excited to implement what we talked about in their own orgs
● Familiar with the challenges being discussed
What should they do differently afterwards?
● Treat their assistants like a product, not a project