Revolutionize data extraction with the GPT-4 powered parser. Extract structured data from PDFs, emails, and documents. Export the parsed data in real time to Google Sheets, CRM, and over 5000 other apps, or create custom automations.
👋 Hey Product Hunt
My name is Andrew, I'm the creator of Airparser.
Airparser is a data extraction tool, powered by GPT-4. I created it to solve the problem of data extraction from unstructured documents.
USE CASES
⚡️ Emails: Extract leads, signatures, contact information, dates.
⚡️ Invoices: Capture amounts, dates, line items.
⚡️ CVs: Extract names, contact information, and work experience.
⚡️ Contracts: Extract terms, parties involved.
⚡️ Order confirmations: Extract order numbers, items, and delivery details.
⚡️ Handwritten texts: Digitize handwritten notes, lists, and more
HOW AIRPARSER WORKS
1️⃣ Import: Import your emails, PDFs, scanned images, Word and other documents.
2️⃣ Extract: Simply describe the data to be extracted, and let Airparser handle the rest.
3️⃣ Export: Export automatically to Google Sheets, CRM, 5000+ other apps, or create custom automations.
FEATURES
✅ GPT-4 powered: Set up in just 2 minutes for effortless efficiency.
✅ OCR engine: Extract data from scanned documents, images and handwritten notes.
✅ Any document: Parse texts, emails, PDFs, images, HTML, and more.
✅ Secure: Your data is securely stored and never used to train GPT models.
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Curious about Airparser? Share your questions, thoughts, or feedback in the comments below!👇
This is a great app,but what's more fun is am now using it and I would like to ask a simple question,those anyone want to be a part of Tesla investment.
The parsing does not extract the element if the element does not have the same keyword, for instance if i say VAT amount and the document has Taxe lebel on the amount, it will not be taken.
Hi Andrew, gratz on the launch.
Airparser sounds like an incredibly useful tool, and it's exciting to see how it leverages GPT-4 to tackle the challenge of data extraction from unstructured documents. The use cases you've mentioned, from emails to invoices, CVs, contracts, and even handwritten texts, cover a wide range of scenarios where people often struggle with manual data entry.
Good luck!
Congratulations on the launch @andrewio . Can this software go through past emails to retroactively extract contact info?
It's obvious you are using pods. The first product of the day is cheating, and nobody cares about that. @adityavsc
Congratulations on the launch Andrew and Hamza, good to see this idea on the #1 position for today!
Andrew, my deep Congrats! Good luck!
I have questions, Andrew)
#1 How do you plan to differentiate Airparser and capture market share, and what strategies are in place to scale the business rapidly
#2!!! How does Airparser ensure compliance with data protection regulations??
#3 what is the specific pricing model?
Andrew, big congrats on Airparser's debut! 🚀 Can you elaborate on how it maintains data precision across various fonts and handwriting styles?
Congratulations, Andrew, on the launch of Airparser! 🚀 This is a game-changer for data extraction from unstructured documents. Impressive use cases from emails to handwritten texts! I'm curious about the accuracy and adaptability of your OCR engine when dealing with various fonts and handwriting styles. How well does it handle diverse document formats? It'd be great to see some use case examples or success stories on your website to showcase how Airparser has helped businesses or individuals in real-world scenarios. 📈
