Tagger is a decentralized artificial intelligence (AI) data solutions platform that utilizes a blockchain-based system for data authentication, collection, labeling, management, and trading. The platform applies Web3 principles and a Decentralized Physical Infrastructure (DePIN) framework to create a permissionless environment for data contribution and verification. ^[11]

Overview

Tagger is designed to address persistent challenges within the data economy, including data silos, inconsistent verification standards, insecure cross-border data exchange, and a shortage of skilled data annotators. The platform's core objective is to democratize access to high-quality, professional datasets, thereby enabling broader participation in AI development. It integrates its decentralized infrastructure with AI data workflows to standardize data authentication, improve data quality, and expand global access to AI-ready datasets.

The ecosystem operates on a foundation of blockchain technology, cryptographic methods, and smart contracts to establish a transparent and secure environment. Digital certificates represent data ownership and intellectual property rights in the form of Non-Fungible Tokens (NFTs), which are recorded on-chain. This system incentivizes a global community of participants to collaboratively contribute and label data. To maintain the quality of these datasets, Tagger uses AI-assisted annotation tools and automated filtering. The platform also features a decentralized marketplace where users can trade, license, or share datasets under verifiable conditions. ^{[1] [2]}

Features

Data Authentication Protocol

The platform's data authentication protocol is a decentralized system that uses cryptography and smart contracts to verify data ownership and rights without a central authority. When a user uploads a dataset, the platform generates an index file, and the owner can mint an NFT to serve as a verifiable certificate of ownership. This NFT grants the holder exclusive control over the dataset, including permissions for viewing, authorizing use, publishing annotation tasks, trading, or deletion. If the data undergoes annotation, the resulting labeled dataset is encrypted and linked to a new NFT, confirming ownership of the enhanced data asset.

For security, Tagger employs a dual-layer chaotic encryption system that combines diffusion and permutation techniques to protect against tampering. This is further reinforced by hyper-chaotic and time-series prediction algorithms to ensure that all datasets remain verifiable, encrypted, and resistant to unauthorized modification. ^[3]

AI Data Collection

Tagger includes a decentralized module for AI data collection that enables users to crowdsource data through a blockchain-based system. When a user creates a data collection task, the platform applies Natural Language Processing (NLP) to analyze the request, match it with suitable data categories, and connect the publisher with Web3 participants who can contribute the required data. Contributors upload their data, which is then verified by Tagger’s AI system to filter out substandard submissions. Upon approval, contributors receive token-based rewards proportional to the quality of their submissions. All contributed data is encrypted using a dynamic, mixed-chaotic system. After the collection is complete, the task publisher can mint an NFT as a tamper-resistant proof of ownership for the dataset. ^[4]

AI Data Labeling

The platform provides a decentralized system for AI data labeling that integrates ownership verification, AI-assisted annotation, and smart contracts. Users who hold a dataset ownership NFT can initiate annotation tasks. The platform's indexing system then matches these tasks with qualified data workers from its Web3 community. These workers access encrypted data via secure decryption algorithms and use AI-supported graphical tools to complete labeling tasks. The system incorporates target-detection algorithms to identify key areas for annotation, thereby reducing manual effort. An integrated AI assistant monitors the process in real-time to help maintain annotation quality. The platform also combines AI models with expert knowledge bases to help workers accurately label specialized datasets. A built-in pixel recognition module evaluates the completeness and quality of annotations to ensure they meet professional standards. ^[5]

Data Evaluation, Cleaning, and Processing

Tagger utilizes an automated framework for data evaluation and processing that employs statistical and computational methods to monitor the accuracy of dataset labeling. When the system detects significant discrepancies in labeling performance, it isolates the relevant data points for review to identify anomalies. The findings from this review process are then used to incrementally retrain the labeling model, allowing it to adapt to new data patterns while maintaining consistent accuracy. This automation is designed to reduce reliance on manual labor, improve efficiency and scalability, and minimize errors and operational costs associated with data cleaning. ^[6]

Data Trading and Management

Tagger operates a decentralized marketplace for the exchange, authorization, and management of AI datasets. The system aims to address challenges caused by inconsistent global data regulations and data silos by providing a standardized protocol for authenticating ownership and facilitating secure transactions. Datasets and their annotations are encrypted, indexed, and recorded as NFTs, which grants owners verified control to trade or license their data. The marketplace also features an "authorization mode" that allows datasets to be used for AI model training without exposing the raw data. This is achieved through privacy-preserving technologies such as federated learning, advanced encryption protocols, and Trusted Execution Environments (TEE). An agent-assisted data management system built on Retrieval-Augmented Generation (RAG) and large language models supports efficient data processing, querying, and analysis. ^[2]

Products

HITL Telegram Mini App

The Human-in-the-Loop (HITL) Telegram Mini App is a gamified application that allows a decentralized community of users to participate in AI training by evaluating AI-generated content. To reduce individual bias and improve the reliability of validation, each task is reviewed by nine different participants. Users earn in-app coins for providing accurate feedback, which can be used to upgrade their abilities, increase task rewards, and generate passive income. The app operates on a seasonal reward model, where active users receive airdrops of the $TAGGER token based on their activity, accuracy, and progression level. This structure integrates decentralized validation with financial incentives to maintain data quality and sustain long-term user participation. ^[7]

Monitoring Wristband

As part of its DePIN strategy, Tagger has developed a health-monitoring wristband. The device collects real-time physiological data from users, including heart rate, blood pressure, temperature, sleep patterns, blood oxygen levels, and other biometric indicators. The data gathered contributes to the development of AI models for health monitoring, with a particular focus on the early detection of cardiovascular and respiratory conditions. Participants who share their data receive token-based rewards, and the data is protected through decentralized protocols to maintain user privacy and security. The resulting datasets and AI models are intended to be made available to international health organizations to support global health research initiatives. ^[8]

TAG

$TAG is the native token of the Tagger ecosystem, earned through proof-of-work contributions from data workers. It serves as the primary medium for activities such as posting data tasks, staking, purchasing or renting datasets, accessing software services, and customizing AI models.

Tagger’s business model connects data workers, individual AI developers, and AI companies to facilitate data processing, management, and transactions. The platform creates and annotates official datasets for sale or rental, while users can publish data-related tasks and compensate contributors with $TAG. Through its data authentication protocol, Tagger ensures secure data ownership and trading, with transactions on the marketplace incurring small $TAG-based service fees. ^[9]

Tokenomics

TAG has a total supply of 405,380,800,000 tokens and has the following distribution: ^[10]

• Proof-of-Human-Work: 74%
• Tag-to-Pump: 21.06%
• Liquidity: 4.93%

Partnerships

• Stables
• Readii
• Blue Sky Carbon
• Huawei Cloud
• Four
• 4EVERLAND
• Buildon Galaxy
• ListaDAO
• Solidus
• Lorenzo