Based on latest advancements in document transformers, what strategy would you use to parse utility bills?

This page summarizes the projects mentioned and recommended in the original post on /r/LanguageTechnology

InfluxDB - Power Real-Time Data Analytics at Scale
Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
www.influxdata.com
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SaaSHub - Software Alternatives and Reviews
SaaSHub helps you find the best software and product alternatives
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  • pdfGPT

    PDF GPT allows you to chat with the contents of your PDF file by using GPT capabilities. The most effective open source solution to turn your pdf files in a chatbot!

  • PDFChatter (Universal Sentence Encoder + GPT-3.5): out of the box, this solution works quite well. However, the need for Q&A prompting (and 'black-box' nature of the solution) seems to disqualify it as an optimal solution.

  • document-ai-samples

    Sample applications and demos for Document AI, the end-to-end document processing platform on Google Cloud

  • Google Document AI: Google's generic document processor, found on the Google Cloud Platform, worked ok out of the box. However, it will require significant fine-tuning via manual data labeling for at least 15 to 20 documents before I have a decently accurate processor.

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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