Fine-tune Amazon Nova models for accurate email data extraction | Amazon Web Services
The authors would also like to thank Karan Bhandarkar, Sue Cha, Yash Shah and Nieves Garcia for their contributions in making this initiative possible.
If you process millions of email messages daily, fine-tuning Amazon Nova models can help you automate accurate data extraction while reducing costs and hallucinations. Parcel Perform, a leading AI Delivery Experience Platform for ecommerce businesses worldwide, faced this exact challenge when extracting structured information from diverse email formats, ranging from simple notifications to complex HTML documents with extensive JavaScript elements.
Common challenges include model hallucinations, confusion between similar data types (such as order numbers and tracking numbers), and prohibitively high token costs when processing HTML-formatted email.
In this post, you’ll learn how fine-tuning Amazon Nova models using Amazon SageMaker AI addresses these specific issues by teaching the models to recognize your exact data patterns, distinguish between similar fields, and process information more efficiently—achieving up to 94.77%...
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