This document discusses Unbabel's approach to providing multilingual customer support through a combination of artificial intelligence and human translators. It describes how Unbabel uses advanced AI to handle large volumes of translations at high speed while maintaining quality through human refinement. Unbabel also utilizes a global network of human translators to provide native-quality translations through a "gig economy" model. The document outlines Unbabel's translation pipeline and how their AI is continuously trained on proprietary data to improve over time.

1. The secret of having
a multilingual
business
Maxim Khalilov, Director of Applied AI
Jan 9, 2020

2. 2
How the web content is
translated?
Unable to scale
to the growing mountains of digital content
Human-only
Lacks the necessary quality
for a reliable customer experience
Machine-only
VS.
Google Translate (2018) -
143 B/day
Humans (~ 500,000 translators
at 3000 words/day) =
1.5 billion words/day

3. 3
Advanced AI
for speed and scalability
The world translation layer built on a hybrid
approach
Gig Economy
for native-quality translation

4. 4
Customer
Service

5. 5
Focus on customer service.
Language matters
84%
Would buy more.

6. 6
Focus on customer service.
Struggling with language barriers.
Manually copy-and-pasting
with translation tools
Asking native speaker
employees for help
Finding bilingual
agents

7. 7
Unbabel Tickets Unbabel Chat Unbabel FAQs
Keep the conversation flowing in your
customer's native language.
Publish and edit self-service content in all the
languages your customers speak.
Translate customer queries with total
confidence, from opening to resolution.
Our products
Our AI-powered, human-refined solution helps you provide cost-effective multilingual
support where your customers need it most.

8. 8
Order Data
Anonymization
Machine
Translation
Quality
Estimation
Translator
Community
Finished
Order
Annotation
Continuous Training
Tickets, Chat, and FAQs
Unbabel Translation Pipeline

9. Decomposing
technology
9

10. 10
The layer
Continuous
learning
Proprietary
data
AI Stack
Seamless
Integrations
Continuous
learning
Proprietary
data
Seamless
Integrations
Gig
economy

11. 11
Domain-adapted NMT
MQM

12. 12
Quality estimation
Original Text Machine translated

13. 13
Quality estimation
Original Text Machine translated

14. 14
Quality estimation: the
state-of-the-art system

15. 15
Value of customer data

16. 1
6
Unbabelers worldwide

17. Unbabelers worldwide
Use of AI
augmented tools

18. 18
Unbabel
for Travel
Industry

19. Company name
5HOne year later
92One year later
17HBefore Unbabel
75Before Unbabel
Case study
Customer SatisfactionFirst response

20. Company name
easyJet centralized Dutch and German live chat
in Delhi with Unbabel
Allowed them to cover Dutch for the first time
A cost saving of 76% compared to native coverage
CSAT is 4.2% higher than languages they provide with native speakers
Significantly more flexible operations
Center of excellence

21. Company name
Potential use cases
Existing customers
Travel
• Centralize non-voice customer service into a
single low cost, high performance centre of
excellence
• Increase language coverage, particularly for
traditionally expensive to cover languages
• Manage localized customer service spikes
more efficiently
• Improve agent utilisation rates
• Reduce overall CS costs
• Hire for knowledge and talent rather than
language
Key benefits

22. Chapter 01
Thank you
Maxim Khalilov
Director of Applied AI, Unbabel
maxim@unbabel.com