Presented by Alan Nichol at the 2021 Rasa Summit See the talk recording on the Rasa YouTube channel: https://youtu.be/LFRQWNfprQU

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8. Confidential and proprietary.
Any use of this material without specific permission of Rasa is strictly prohibited.
Conversational Teams:
Moving Fast at Scale
February 2021

9. 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

10. AI Assistants involve machine learning
That doesn’t mean we should throw out everything
we know about shipping good software.

11. The many faces of scale

12. Successful assistants will scale to a larger user base

13. And will expand to help users in new ways
Check balance Money transfer

14. They get deployed on different channels and in multiple languages

15. The teams supporting them grow and divide, and include many different roles

16. And teams will share functionality across assistants
* greet
- Hi
- Hello
* goodbye
- Bye
- See ya
Financial bot
Sales bot

17. Move fast and scale things

18. Good news: a lot of this has already been figured out, and you’re (hopefully)
already doing much of it.
Most best practices from shipping software products translate well to conversational AI

19. Feels like going faster Actually makes us faster
Learning from real conversations
Changes go live right away
Building on customizable infrastructure
Changes go live after review & automated tests
Versioning both together for reproducibility
Composing at build time
Generating lots of synthetic training data
Using a black box tool that hides the details
Separating code & content
Composing at run time

20. Accelerate RoI by learning from real users as early as possible.
Putting CDD to the test (Rasa Blog) CDD Playbook (website)
Generating lots of synthetic training data Learning from real conversations

21. Use the latest research and choose the model that works best for you.
≈≈
Plug and play language models like BERT and GPT-2 into
DIET, or bring your own embeddings.
DIET has been used to train NLU models in 60+ languages!
Using a black box tool that hides the details Building on customisable infrastructure

22. #232a2e
Spend time on enhancements instead of fixing bugs introduced last week.
Changes go live right away Changes go live after review & automated tests
Separating code & content Versioning both together for reproducibility

23. Reliably share the load across teams by sharing code and composing at build time.
money_transfer:
- I want to transfer money
- I want to make a transfer
Financial bot
loan_queries:
- I need a loan
- I want to take out a loan
Composing at run time Composing at build time
Insurance bot
Main bot
Financial bot
Microservices only work if you can enforce a strict API between components. That’s not how people talk.

24. Scaling your Ambition

26. A scalable foundation for grand designs.
PRODUCT
Consistent across every touchpoint, easily evolved
with new and better skills and actionable insights
A brand conversation and
customer experience
Company
Customer

27. Alan Nichol
Co-founder & CTO
alan@rasa.com
@alanmnichol
Email me! →
alan@rasa.com