Label Your Data

Data annotation solution for ML datasets

219 followers

Data annotation solution for ML datasets

219 followers

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Data analysis tools

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AI Infrastructure Tools

Label Your Data helps with annotating datasets for ML models. Useful for AI engineers working with computer vision. Upload your dataset and track its labeling progress. Try it yourself

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Launch tags:Artificial Intelligence•Data•Data Science

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Label Your Data

Maker

🎉 So proud to share what our team has built! 🔥 This is exactly what the industry needs! The straightforward process, starting with sample results and leading to cost estimates, removes so much friction from data labeling. For startups and small teams, this is a game-changer - affordable, intuitive, and built for scale. 🚀 We delivering a tool that balances simplicity with power. A great solution for ML practitioners! Affordable, flexible, and scalable - it’s everything a modern team needs. Here’s to revolutionizing data annotation! 🌟 🙌 Finally, a data labeling tool that doesn’t break the bank or complicate the process! This platform is such a win for indie developers, small teams, and even academic researchers who need a reliable, cost-effective solution. From sample results to API integration, everything about this feels designed with the user in mind. Excited to see where this journey takes the team - amazing work! 🚀 Your feedback is invaluable - let us know what you think, and help us shape the future of data annotation! 🚀

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2yr ago

Label Your Data

Maker

The ability to easily upload datasets and track labeling progress makes this platform a valuable tool for improving and simplifying workflows. Congratulations on the launch and I hope it helps many people with their projects! 🎉

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2yr ago

Wasp

Good luck with the launch, folks! Product looks super interesting and obviously has a niche, especially in GenAI era. Best of luck!

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2yr ago

Label Your Data

Maker

Big congrats to the team on the launch! 🎉 The clean UI and API integration are spot on – they really streamline ML workflows. The cost calculator and free trial are great additions, making it easy to get started and see the value right away. Excited to see how the platform expands beyond computer vision in the future!

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2yr ago

@karyna_naminas1 @osnovyanenko Congrats on the launch! 🚀 You guys did an amazing job by simplifying data labeling and annotation for startups and ML engineers. The platform is super intuitive and user-friendly. You've really cracked the code on a clear pricing model and transparent cost estimate 😍 I haven't seen anything like it yet, and I highly recommend it to all ML players in GenAI era!

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2yr ago

Softorino 💻📲

Wow! @karyna_naminas1 🎉 Congrats on the launch! I think the free sample results will be super helpful for teams handling large datasets. How soon do you plan to add NLP and LLM support?

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2yr ago

Label Your Data

Maker

@bdzhel great question! This is our plan for 2025. The ability to fine-tune and customize your LLMs, as well as integrate the labeling workflow directly into your ML Ops platform, is what we will be rolling out next.

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2yr ago

Softorino 💻📲

@karyna_naminas1 I feel like LLM annotation will be the big thing. Hope you guys release it soon :D

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2yr ago

Great to see a streamlined solution for annotating datasets in the computer vision space! The ability to track progress and receive a cost estimate is a big plus. How do you ensure the accuracy and quality of labeled data, especially for larger datasets?

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2yr ago

Label Your Data

Maker

@hritik_choudhary Great question—thank you for asking! We have an internal QA process in place to ensure the accuracy and quality of labeled data, regardless of the dataset size. Here's how we approach it: 1️⃣ Expert Review: All annotations go through an additional layer of review by experienced QA specialists to ensure consistency and accuracy. 2️⃣ Spot Checks: For larger datasets, we conduct random sampling and spot-check annotations to catch and correct potential errors early. 3️⃣ Feedback Loops: Our platform allows users to provide feedback on annotations, which helps us continuously refine and improve the quality of our work. This multistep process helps us deliver reliable, high-quality labeled data while scaling up efficiently. 😊

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2yr ago

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