With onetask, you can label AI training data on large-scale yourself. We combine Weak Supervision and Active Learning, so that you can easily find patterns in your data and only label records by hand that need human cognition.
Hey Product Hunt Community, we are super thrilled to present to you onetask, our solution for large-scale labeling.
We are a team of eight young Data Scientists from Germany, and we were unhappy with the labeling tools there are. Labeling is typically either highly time-consuming and therefore expensive, needs subject matter expertise and is thus restricted, or oftentimes is just way too intransparent.
onetask is our approach to make this better, by providing a tool that helps you explore your data, find explicit patterns, and use them to label on large scale. This way, we believe that data labeling can actually be built and debugged. You know where strengths and weaknesses in your labeling will be and can act on those insights.
Currently, the solution is best suited for any classification case in which you have some sort of unstructured text or structured metadata, e.g. messages, machine-readable documents, sensor data and many more.
Our solution is available in a closed beta version. It is completely free to use, and we'll help you get on board. If you have interest in our solution, let me know! :)
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