AnnotateAI

Human-guided AI data annotation, fast & scalable

58 followers

Human-guided AI data annotation, fast & scalable

58 followers

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AI Infrastructure Tools

AnnotateAI is a human-guided, agentic data annotation platform for computer vision teams. Upload your dataset, auto-create annotation jobs, track progress in real time, and intervene whenever precision matters. Get high-quality, model-ready data faster with AI speed and human control, built to scale from experiments to production.

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Launch tags:SaaS•Developer Tools•Artificial Intelligence

Launch Team

EneyProactive AI for Mac. Free test, 20,000 credits.

Promoted

Coderrr

Maker

📌

Hey Product Hunt! 👋 I’m Akash, the maker of AnnotateAI. I built this after struggling with slow, manual data annotation while training computer vision models during hackathons and projects. Most tools were either fully manual, expensive, or removed human control completely, and that trade-off between speed and accuracy kept hurting my workflows. So AnnotateAI is my take on a better approach: ⚡ AI-assisted annotation for speed 🧑‍💻 Human-in-the-loop when precision matters 📦 Upload a ZIP → auto job pipeline 📊 Real-time job tracking 🔁 Built to scale for large datasets It’s designed for students, researchers, and ML teams who want model-ready data without annotation becoming a bottleneck. We’re still early, and your feedback will directly shape what comes next — especially around new annotation types, team collaboration, and active learning loops. If you work with CV datasets, I’d love to know: What’s the most painful part of your annotation workflow today? Thanks for checking it out and supporting the launch ❤️ — Akash

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8mo ago

Burner

The real-time intervention piece is what makes this worth paying attention to — to add to the point about stop signs, edge cases in annotation are where models quietly learn the wrong thing, and catching that mid-job rather than post-training is a meaningful workflow difference. Curious how AnnotateAI handles disagreement between the AI's labels and the human reviewer — does that signal get surfaced anywhere, or is it just a correction and move on?

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7mo ago

Coderrr

Maker

@wcrtr Keeping fast prototyping in mind, I kept it pretty straight forward. User corrects and moves on.

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7mo ago

auto-annotation cool
til your model learn nonsense

human in the loop ain’t weakness
that’s control

speed without discipline?
just faster mistakes

data clean > hype loud

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8mo ago

Forum Threads

p/annotateai

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8mo ago

Announement

Hey everyone!

I m excited to share something I ve been building AnnotateAI: a platform that helps you turn raw image datasets into high-quality, model-ready annotations faster, using AI + human-in-the-loop.

While working on computer vision projects, I kept hitting the same bottleneck annotation was either:

fully manual and slow, or
automated but hard to control and verify.

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