Life & fun · September 30, 2025
Document extraction with human feedback loop
About the feature: We built a tool for automatically assessing business health from complex management financial documents and bank statements. In order to get this working reliably, we had to iterate extensively on the prompts for the structured output at the field level. This led us to building a feature to allow users to improve them too, and with some context engineering, we have what we are calling “feedback loops”. Here is a 2 min demo https://www.youtube.com/watch?v=ZDNlEZydoXU How it works (video runs through these steps): 1. Create a target form for your extraction…
What it does
In the maker’s words, at launch
About the feature: We built a tool for automatically assessing business health from complex management financial documents and bank statements. In order to get this working reliably, we had to iterate extensively on the prompts for the structured output at the field level. This led us to building a feature to allow users to improve them too, and with some context engineering, we have what we are calling “feedback loops”. Here is a 2 min demo https://www.youtube.com/watch?v=ZDNlEZydoXU How it works (video runs through these steps): 1. Create a target form for your extraction (AI helps create it) 2. Upload a document (choose from different models) 3. Review the quality of the extraction (and check the PDF citations) 4. If there are any mistakes, correct them and give feedback at the field level 5. Once you feel like you've seen enough errors and provided enough corrections, use the Feedback workflow to refine your field descriptions. You can try the app here https://app.sea.dev/ (it works best when you do at least 2-3 reasonable extractions between prompt refinements) The feedback feature is currently in beta. If you make some corrections and then go to https://app.sea.dev/feedback you'll see them ready for review and refinement. I would love to get feedback on how we might improve this idea. The video was a toy example but it is live and working with a few early credit analysts customers and they seem to like it.
Does the same job
all alternatives →

- IEImpraise – Easy continuous feedback at work (YC S14)2014 · impraise.com · ▲47

- ALA labelling tool to easily extract and label Wikipedia data2021 · ▲116
Hi HN! I am Maria, solo founder of DataQA (https://dataqa.ai/), a tool to search and label documents for various NLP tasks (e.g. entity extraction, entity linking, etc). I have worked as a data scientist and ML engineer for the better part of a decade, and over that time have specialised mainly in applications involving natural language processing (NLP). One of the key questions I have always had at the back of my mind is whether my time was well spent. Whenever I spent more time on feature engineering or trying different models, I always wondered whether I would get better…
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