The annotation of data provides a key element that will contribute significantly in the development of efficient and effective machine learning models. However traditional systems for awarding data annotation have difficulty performing this function because of payment security issues, fraudulent listings, and excessive storage burdens. To solve these challenges, we propose LabelChain. a blockchain-based solution for labelling datasets. It supports decentralized verification and multilingual payload for authentication, and it uses AWS public cloud storage to store data as images. The model is based on a Solana blockchain framework that is used by the community to verify transactions. Tasks are assigned validated images and paid via the network. To enable transparency as well as automation of the task, we use presigned URLs for photo upload, and to avoid any privacy problems with the data, we use an AWS S3 protocol and allow photo upload only after verification. Once a payment has been sent, tasks are shared locally in the AWS CDN which provides low latency and consistent access to users.