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How to Streamline Archival Research with a Custom AI-Powered iOS App

Develop a custom iOS app like 'Flip Flop' to streamline research in physical archives. Use AI to automatically describe and transcribe photos of documents and embed the data directly into the image files.

From How I AI

How I AI: Tim McAleer's AI Workflows for Documentary Filmmaking at Florentine Films

with Claire Vo

How to Streamline Archival Research with a Custom AI-Powered iOS App

Tools Used

Claude

Anthropic AI assistant

ChatGPT

OpenAI conversational AI

Step-by-Step Guide

1

Define App Requirements with an LLM

Describe the screens, user flow, and core features of your desired research app in plain language. Use a tool like ChatGPT to transform your description into a formal Product Requirements Document (PRD).

2

Generate UI Code with an AI Assistant

Feed the detailed PRD into a code-generation model like Claude. Prompt it to write the Swift code needed to build the app's user interface, providing a strong foundation for development.

3

Implement the Core Capture Workflow

Build the main functionality of the app. A user should be able to create a collection, take a photo of the front of a document, and then immediately tap a button to capture the 'flop' (back) side, ensuring the two images are linked.

4

Integrate AI for Description and Transcription

Connect the app to the OpenAI API. Set up an automated process where, upon capture, the front image is sent for a visual description and the back image (which may contain handwritten notes) is sent for transcription.

5

Embed AI-Generated Data into Image Metadata

Program the app to write the AI-generated description and transcription directly into the EXIF metadata of each image file. This makes each photo a self-contained, data-rich asset that is already organized and searchable when transferred from the device.

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