The Smart Workflow: Batch-Titling Images with Context-Driven AI
In our previous guide, we established that providing detailed context (Who, What, Where, When) is the key to generating perfect titles for individual images. But what happens when you have hundreds, or even thousands, of photos from a single event, photoshoot, or trip? Manually creating context for each image is impractical.
We suggest a simple but powerful best practice: organize your projects into descriptively named folders. This habit solves two major problems at once. First, your own photo library becomes instantly organized and searchable.
Second, PhotoTager uses that folder name as the perfect context. It can then generate accurate, consistent titles and keywords from 10-100 images at once inside that folder. You solve your organization problem and your metadata problem in one go, simply by naming your folders well. This is how you SCALE UP
This guide will show you how to structure your images in a way that allows you to provide context once for an entire group of similar photos. We do this by organizing images into Projects and processing them together as a Batch.
The Core Concept: From Single Image to Project Folder
The fundamental shift is from a one-to-one to a one-to-many relationship:
- Before: 1 Context → 1 Image
- Now: 1 Context → Many Similar Images
We achieve this by using a method you likely already know: organizing files into folders. In this workflow, the folder itself becomes the context.
- Project: A subfolder containing a group of similar images from your shoot. The name of this folder is the detailed context for every image inside it.
- Batch: The main parent folder that contains all your individual "Project" subfolders. This is the entire job you will upload for processing.
Step-by-Step Guide: How to Build Your Batch
Follow these steps to turn a chaotic collection of photos into a perfectly organized, AI-ready batch.
Step 1: Sort Your Images
Go through all the photos from your shoot. Group them based on shared context. All the photos of the bride getting ready go together. All the photos of the keynote speaker on stage go together. All the wide shots of the mountain landscape go together.
Step 2: Create Your "Project" Folders
For each group of similar images, create a folder. Now, name that folder using the Who-What-Where-When framework. This is the most important step. Use clear, descriptive natural language with information that cannot be infered from the image and only you know.
Example Folder Name:
WHO-WHAT-WHERE-WHEN-description
Practical Examples:
- For photos of a local festival:
Kurenti performers dance in Traditional parade, Ptuj Slovenia Kurentovanje Festival 2025 - For photos from a corporate conference:
CEO Janez Novak Giving keynote speech In Cankarjev Dom Ljubljana at Annual-Tech-Summit - For photos from a family trip:
Novak family children are Playing in snow inKranjska Gora in a Winter afternoon
Step 3: Assemble Your "Batch"
Create one main folder to hold all your new "Project" subfolders. Give this "Batch" folder a clear, high-level name.
Example:
📁 Slovenian-Festivals-2025-Shoot/
L 📁 Kurenti performers .../L 📁 Ljubljana marathon runners .../L 📁 Midsummer bonfire attendees .../
Step 4: Upload and Process
Now, you can simply upload the entire "Batch" folder to the PHOTOTAGER AI processing system. The system will read each "Project" folder, understand its name as the context, and apply that context to every image inside that specific folder.
The Magic: How the AI Intelligently Applies Context
Here is the most powerful part of this workflow. The AI uses the context from the folder name as a pool of available information, not as a rigid template. It intelligently selects only the relevant details for the specific image it is titling.
As you noted, if the context mentions a person who isn't visible in a particular shot, the AI will ignore that piece of information for that title.
Let's imagine your "Project" folder is named:Chef Luka and team preparing seafood risotto at JB-kitchen Restaurant
Inside this folder, you have several images:
Image A: A wide shot showing Chef Luka directing his team around a stove.
AI Title: "Chef Luka directs his team in the kitchen at Restaurant JB during a busy dinner service as they prepare seafood risotto." (Uses all context).
Image C: A macro shot of the finished risotto, beautifully lit. No people are visible.
AI Title: "A beautifully presented plate of seafood risotto from Restaurant JB." (Ignores all "Who" context and focuses on the "What").
This "selective application" ensures that every title is not only contextually rich but also visually accurate, saving you an enormous amount of time on corrections. You provide the rich story once per project, and the AI tailors the details for every single photo.