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DeepTagger: A No-Code Platform for Extracting Structured Data from Documents Using Interactive Labeling

Talshyn Nova

8mo ago· 1 min readenProduct

38/100

Stale

Bagelometer↗

Has the shape of a bagel but none of the steam.

Score38Typepress releaseSentimentpositive

Summary

DeepTagger is a no-code platform born from the challenge of extracting structured data from the Enron Email dataset during a PhD project. The creators struggled with custom parsers, RegEx, and traditional ML tools like spaCy Prodigy and Label Studio when trying to split long email chains into individual emails. They built their own annotation tool that uses user annotations as examples to extract information from new documents, making human judgment scalable through an API-accessible platform.

Key quotes

· 5 pulled

This product was born out of real-life problems.

Custom Python parsers failed. RegEx broke.

Traditional ML tools, such as spaCy Prodigy, or Label Studio, couldn't handle the complexity.

Doing it manually would have meant admitting defeat.

So we built our own annotation tool that could handle nested

Snippet from the RSS feed

DeepTagger is a no-code platform that makes your judgment scalable. It uses your annotations as an example to extract information from new documents. Highlight what matters to you once, and let DeepTagger handle the rest with precision. API access include

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