# Amazon Textract Projects at AI Tinkerers

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> Technology record last updated: 2026-02-25T04:12:55Z
> Generated: 2026-09-21T09:45:53Z

Amazon Textract is a machine learning service that automatically extracts text, handwriting, and structured data from virtually any document.

Textract is your fully managed AWS machine learning service for document data extraction. It goes beyond standard OCR (Optical Character Recognition) to intelligently identify and extract structured elements: tables, forms (key-value pairs), and even handwriting. Use the Analyze Document API to process complex documents like invoices, medical records, or loan applications. For example, Anthem automated over 80% of its claims processing workflow using Textract, moving data from millions of documents into actionable formats without manual configuration. This service delivers high-accuracy, scalable document intelligence, ensuring you only pay for what you process.

- Official technology site: https://aws.amazon.com/textract/
- Public AI Tinkerers demos and talks: 5
- Result page: 1 of 1

## Recent Public Talks and Demos

### [From Image to Structured Data: Building a Local AI Document OCR Platform for Administrative Workflows](https://tokyo.aitinkerers.org/talks/rsvp_Vs-o12h3f_U)

Administrative and compliance-heavy professions still rely heavily on paper and scanned documents. However, sending sensitive documents to cloud OCR or AI services is often not acceptable due to privacy, regulatory, or client confidentiality requirements. In this talk, I will present a professional web-based OCR processing platform designed for secure, local-first document handling — with a focus on real-world administrative document workflows such as those handled by 行政書士 professionals.

- Event context: AI Tinkerers Tokyo - Toranomon Meetup - February 19, 2026 — 2026-02-19 — Tokyo
- Public talk page: https://tokyo.aitinkerers.org/talks/rsvp_Vs-o12h3f_U

### [The Future of Taxes](https://st-louis.aitinkerers.org/talks/rsvp_WsQcRPj15Rg)

My startup company is developing a tax AI product called Fiscal Mind. The idea is for CPAs to have clients take photos of their tax documents and upload it and once we have enough fiscal data then we calculate their taxes owed and also suggest ways for the next year on how to lower tax costs slightly. This streamlines the process and saves over 70% of a CPA's time since typical tax filings can take anywhere from 8 hours to 5 days. It is meant as an assistant not to completely take over.

- Event context: AI Tinkerers – St. Louis Meetup: February 4, 2026 — 2026-02-04 — St. Louis
- Public talk page: https://st-louis.aitinkerers.org/talks/rsvp_WsQcRPj15Rg

### [AI Professional Network Builder](https://hong-kong.aitinkerers.org/talks/rsvp_7r5C0zv1pcs)

In this demo, I will go through the product itself, solution architecture, and lesson learnt from vibe coding a product, below are some background info of the demonstrated product: Business Card Scanner: Digitize and Analyze Your Professional Network with AI The Business Card Scanner is a web application that transforms physical business cards into organized digital contacts using AI-powered text extraction and analysis. It helps professionals efficiently manage their network by automatically extracting contact information, categorizing companies by industry, and providing network intelligence through interactive visualizations.

- Event context: AI Tinkerers Hong Kong with AWS Meetup — September 29, 2025 — 2025-09-29 — Hong Kong
- Public talk page: https://hong-kong.aitinkerers.org/talks/rsvp_7r5C0zv1pcs

### [Applying 4o Vision Finetuning to Chemistry Diagrams](https://singapore.aitinkerers.org/talks/rsvp_7w9joR3W_oI)

The task is to extract student's attempts for chemistry diagram questions. These diagrams are a graph with nodes and edges. Using VLLMs out of the box often results in the model correcting the chemistry equations or missing key notation. Here we explore Vision Finetuning, and see how far we can go with less than 10 hand-labelled examples. Kuang Wen and I will show the data we have, the augmentation techniques, and our current demo app comparing finetuned with non-finetuned.

- Event context: AI Tinkerers Singapore: 3rd Meetup - November 19th, 2024 — 2024-11-19 — Singapore
- Public talk page: https://singapore.aitinkerers.org/talks/rsvp_7w9joR3W_oI

### [ML Generated Docs through Video Understanding](https://seattle.aitinkerers.org/talks/rsvp_Rd7nRlt5Gbs)

At Augmend we're developing ways to capture knowledge when devs work. We recently began experimenting with a new feature where we are able to auto-generate documentation just from "watching" your workflow. This allows for things like creating markdown for a how-to wiki without actually having to write anything or capturing the steps you took to solve a problem without taking notes yourself.

- Event context: AI Tinkerers Seattle - August Meetup — 2023-08-09 — Seattle
- Public talk page: https://seattle.aitinkerers.org/talks/rsvp_Rd7nRlt5Gbs

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