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How BLEND Maximized Cost Savings with TAUS Estimate API
Biggest cost savings since the introduction of translation memories
“TAUS has been a great partner to work with. The conversations are engaging, transparent and result-oriented. With the API designed to be both simple and flexible, it allowed us to deploy across various use cases. It enabled us to create a complete workflow layer and solution for our clients to leverage up to 80% cost savings on the translation process.”
The Client
The Challenge
The Solution
The Result
Blend
BLEND is a leading global language service provider known for its advanced machine translation capabilities and commitment to AI-driven localization. Leveraging cutting-edge MT technology, BLEND serves a diverse range of industries, enabling clients to reach international markets with speed and precision. As a leader in the language industry, BLEND continuously innovates its workflows to enhance translation quality, streamline processes, and meet the growing demand for efficient, scalable solutions.
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Uber’s Customer Care Platform
Uber’s Customer Care platform (Support platform) presently supports content across multiple business sectors, including Uber Mobility (Rider, Driver), Uber Delivery (Eater, Courier, and Merchants), Uber For Business (Organizations and Employees), Uber Freight (Carrier, Shipper). Support content is translated with MT engines into and out of more than fifty languages. The platform facilitates the experience for hundreds of content creators, strategists and specialists who produce the support content. Furthermore, it is used by thousands of agents who incorporate the authored content into their daily handling of support tickets, and by millions of users who access it as an essential part of their support experience.
Uber’s challenges
Human review at a global content scale is unthinkable, costly, and time-consuming.
Uber is seeking to address several challenges with the Support Content platform, focusing on improving content quality and effectiveness through personalization, relevance, empathy, and user sentiment. These challenges include:
1- Can we filter out bad machine translated support content before it reaches our customers?
2- Can we measure and enhance the “robotic machine translated score” of the support content?
3- Can we measure and improve the user sentiment when interacting with support content?
4- Can we personalize the tone and voice of the content (e.g., transitioning from informal to a more formal structure) to suit the customer’s conversation patterns?
5- Can we identify and highlight content clean-up actions for content strategists and admins?
6- Can we automatically suggest the creation of new content based on data from our customer tickets?
7- Can we enhance content authoring with auto-suggestions, flag inconsistencies in grammar/tone/voice, recommending similar content, etc.?
The TAUS Estimate API solution
In October 2023, Uber’s localization team integrated the TAUS Estimate API into the Bliss Content Platform. TAUS’s team has customized QE models for multiple languages utilizing its vast repository of in-domain data. Every chat outbound message and support article are now evaluated using a TAUS QE score, achieving 85% accuracy compared to human evaluation. The TAUS Estimate API processes approximately half-a-billion characters every month returning scores in real-time. With this, the first objectives have already been realized: poor machine translations are filtered out, and all support content is scored, providing Uber’s team with a strategic tool to begin enhancing the customer experience.
In the 2024 roadmap, the focus is on expanding the language set with QE scores, and analyzing lower-quality graded support content by utilizing data and models to personalize voice and tone. The goal is to identify and clean up poor content, such as offensive language, improve the source language before it is machine-translated, and retrieve new content from language models. The TAUS NLP team continues to work closely with the Uber globalization team to optimize results from Large Language Models and to further expand on use cases and opportunities offered through AI
About TAUS Estimate API
The TAUS Estimate API provides real-time insights into your content quality, reducing the need for human review and enabling rapid assessment and deployment of accurate language models. The Estimate API seamlessly connects to your content workflows and provides quality scores customized with your data so the results match your organization for accuracy, tone, and authenticity.
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