Data Labeling Platform

The core value proposition here is human judgment at the edge cases. Label Your Data sells a managed annotation team, not software you operate alone — you upload data, choose an annotation type, the team labels it, and you track progress inside the platform. The annotation type list is broad for a managed service: bounding boxes, polygons, cuboids, keypoints, semantic, instance and panoptic segmentation, plus video, image, 3D point cloud, aerial and satellite data, and on the NLP side text entities, characters, audio and content moderation. The operational tooling that supports that work is where the platform differentiates itself from pure service bureaus. The Instruction Generator lets you build annotator guidelines from a pre-made template, which matters because vague instructions are exactly what produces inconsistent labels at scale. The Cost Calculator walks through application field, annotation method and object count to return an approximate total before you commit, and the free task on 10 images or frames lets you evaluate quality on your own data first. The five-step flow — create project setup, run a free task, upload remaining data, track progress, download annotations — is deliberately short. Strengths: published starting rates for keypoints and NLP give you a budgeting anchor instead of a pure request-for-quote; the stated absence of setup fees and long-term lock-ins, with team capacity you can adjust as you scale, suits project-based work; and project leads who came up through annotation work understand where guidelines break. Customer quotes specifically credit turnaround time, annotation quality, responsiveness of feedback loops, and a lack of upselling, while one reviewer notes instructions are sometimes unclear — a fair reminder that guideline iteration is part of the engagement. Weaknesses and boundaries: throughput is bounded by the annotation team, not by compute, so this is not the route to instant, fully automated labeling. Published per-object pricing is specific for keypoint annotation and NLP entities; other annotation types go through a custom calculation, so an exact figure for cuboids or panoptic segmentation requires a conversation. The free pilot sample of 10 images or frames is small relative to production scale, which is why the free pilot is described as a quality test rather than a full trial. And you cannot self-host the labeling operation.