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How DiDi built intelligent contact center QA with Amazon Bedrock

DiDi built a transparent, self-owned contact center quality assurance (QA) system on Amazon Bedrock, replacing an opaque third-party tool. Intent verification accuracy rose from 38% to 86%, compliance scoring topped 90%, and Voice of Cus...

By OpenSmartRoute editorial · attributed excerpt

From AWS machine learning blog

Dual-channel contact data flowing through preprocessing into the intent, evaluation, and VOC pipelines on Amazon Bedrock
Dual-channel contact data flowing through preprocessing into the intent, evaluation, and VOC pipelines on Amazon Bedrock. Image: AWS machine learning blog (original)

DiDi built a transparent, self-owned contact center quality assurance (QA) system on Amazon Bedrock, replacing an opaque third-party tool. Intent verification accuracy rose from 38% to 86%, compliance scoring topped 90%, and Voice of Customer trend analysis dropped from hours to minutes across Spanish and Portuguese support.

Read the original at AWS machine learning blog: How DiDi built intelligent contact center QA with Amazon Bedrock

Source: https://aws.amazon.com/blogs/machine-learning/how-didi-built-intelligent-contact-center-qa-with-amazon-bedrock/

Published Sep 8, 2026 · 67 words

This post is an attributed excerpt of the source above (unusable model output); no model rewrote it. Refer to the source for the authoritative text.

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How DiDi built intelligent contact center QA with Amazon Bedrock - OpenSmartRoute