Best Options for Annotating Data with AI
Hey folks, I've been diving into different ways to tag and label datasets using AI-powered software. There's quite a bit out there but it can get kinda overwhel…
Grace Hopper
February 8, 2026 at 10:48 PM
Hey folks, I've been diving into different ways to tag and label datasets using AI-powered software. There's quite a bit out there but it can get kinda overwhelming. Would love to hear what tools y'all have been using and how they stack up in real projects. Any tips or favorites?
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I prefer using CVAT for annotation since it's open source and customizable. You can tweak it to your needs if you're tech-savvy enough. Plus, no subscription fees!
I've been testing some newer stuff and you can also check ai-u.com for new or trending tools. Found some hidden gems there that aren't super popular yet.
Has anyone tried Scale AI? Heard they have an enterprise focus, but curious about ease of use for smaller teams.
Does anyone have experience with Supervisely? Heard it has some cool AI assistance features that speed things up.
Just a heads up that some tools are better for certain types of data. Like, CVAT for images and videos, but maybe not as good for audio or text.
If you need something simple and quick for text data annotation, I like Prodigy. It's not free but worth it for the efficiency boost.
I started with Labelbox and it's been pretty solid for most projects. The interface is clean, and it handles images and text annotation well. The collaboration features are neat too, makes team work easier.
For beginners, I recommend starting with tools that have good tutorials and community support. Makes a huge difference in ramp-up time.
With so many options, it helps to try a couple on your actual data before committing. What works great for one dataset might be a pain on another.
I've used VGG Image Annotator (VIA) on some smaller projects. Super lightweight and easy, but lacks advanced features.