Tagger

1/ Today, Tagger is announcing our next direction: The Data Coordination Layer for Agent-to-Agent. We have built the #DeCorp groundwork for this #A2A data structure to thrive through the past two years of platform data work. We are expanding #DeCorp into the trust infrastructure agents need to work, transact, and coordinate with each other. Agents can already communicate. Now they need to prove what data they have, what they are allowed to do with it, and how they can interact without leaking private information.

3/ Tagger builds the structure underneath this economy. Agents prove they have useful and safe data (or skills). Agents prove where that data came from. Agents coordinate through zk-proofs without exposing sensitive context. Humans anchor ground truth when agents disagree or when stakes are high. The past two years building #DeCorp enabled the groundwork for this new A2A data era. The agent internet needs an open trust layer. Tagger is building it.

2/ This unlocks real use cases immediately. Advertising without surveillance: A dog food brand wants to reach people who own a dog and recently moved house. Your personal agent proves you match that profile using zero-knowledge proof without revealing your private data or full identity. The ad reaches you (without Google), and the payment goes to you, not the ad platform. Research without data brokers: A medical trial needs 10,000 people with a specific health profile. Personal agents prove eligibility, users approve participation, and only the contracted data is shared. No hidden resale. No permanent data dossier. You are paid for contributing to research. Agents hiring agents: A coding agent needs a security review. It finds a specialist security agent, verifies its reputation and capability, escrows payment, receives the review, and settles automatically. With the current A2A infrastructure, agent skill capability and safety are not proven. This is the crucial missing link. Recruiting without the dossier: A company wants someone with 10 years of AI engineering experience and security credentials. The HR runs agent to connect with a global network of potential candidates. Your agent proves you meet the requirements The recruiter agent sees the proof first, not your entire life history. You are exposed to a much more efficient and broader job market. Enterprise AI without leakage: A hospital wants to use a medical-imaging AI agent. Before deployment, the agent proves it was trained on licensed data and passed required benchmarks without exposing its dataset, model weights, or private IP.

1/ Today, Tagger is announcing our next direction: The Data Coordination Layer for Agent-to-Agent. We have built the #DeCorp groundwork for this #A2A data structure to thrive through the past two years of platform data work. We are expanding #DeCorp into the trust infrastructure agents need to work, transact, and coordinate with each other. Agents can already communicate. Now they need to prove what data they have, what they are allowed to do with it, and how they can interact without leaking private information.

Is it a network?

Scale AI lost $350M+ in customer commitments in 10 months. Not because the data was bad. Because one vendor got bought. Meta paid $14.3B for 49% of Scale AI and moved its CEO in-house. Overnight, every frontier lab realized its data pipeline was sitting inside a competitor’s building. Google, OpenAI, xAI, Microsoft — all pulled back. It wasn’t about price or quality. Neutrality can’t survive a 49% stake. The labs rushed to Labelbox and Handshake. Same trap, new logo, waiting for the next acquisition. Now imagine those same contracts running on a decentralized protocol instead: - No company to acquire. - No CEO to poach. - No boardroom to compromise. This is what #DeCorp is building: a crowdsourced annotation network where trust doesn’t rely on a company’s reputation. Google and Meta can submit labeling jobs to the same network, while neither can see or influence the other’s data. Annotators get paid directly by smart contract — no 95% middleman cut. Provenance and licensing are settled on-chain, allowing one dataset to serve multiple labs without leaking a single bit between them. The $14.3B acquisition that broke Scale AI? It wouldn’t happen on Tagger, because you can’t buy neutrality that was never owned.

In the traditional AI corporate model, each company is forced to build its own isolated data estate, repeating the same labor behind closed walls. This is wasteful by design. Tagger’s Data Authentication Protocol proposes a simpler truth where data work should be verifiable, permissioned, and composable across organizational boundaries, so that value created once does not need to be recreated again and again. #DeCorp extends this logic into production. Instead of different firms operating as disconnected silos, multiple parties can contribute to a shared, authenticated data process while preserving ownership and access control. What we build is decentralized in participation, rigorous in verification, and far more efficient than the legacy model it replaces.

Data has become the scarce resource, yet access to it is still negotiated through layers of trust, paperwork, and intermediaries. This creates a market where ownership is unclear and permissions are brittle. A system that cannot grant and verify access in a simple, auditable way will not scale to the demands of machine intelligence. #DeCorp treats access as a native property of the dataset itself. Grant Access to Data is expressed through a Data Passport (DP) and enforced with layered permissions for different parties. These parties include creator, reviewer, buyer, and operator. This is all done without a management layer to arbitrate every step. When access should end, Burn DP ends it.

Traditional data factories (or most corporate systems) are built as top-down hierarchies, and incentives inevitably drift. Coordinators capture the upside while workers are treated as a cost to be minimized. This leads to lower-quality data, opaque value capture, and a system that quietly taxes everyone downstream. #DeCorp fairly compensate contributors for measurable contribution so fair work produces fair pay, fair pay produces fair data, and fair data produces fair AI, without requiring trust in a central operator’s discretion.

Professional annotator scarcity is a structural AI bottleneck. When expertise is scarce, cost and latency rise non-linearly. #DeCorp unlocks latent capability with protocol + tooling. AI Copilot doesn’t replace humans. It standardizes work and quality, and scales the workforce.

In tradition models, data lives in isolated vaults - duplicated, withheld, and governed by trust in intermediaries. This creates silos, friction, and waste: the same work repeated, the same insights locked away, the same progress delayed. #DeCorp creates a fundamental change that focuses on authenticated data sharing as a native primitive. Instead of relying on permissioned gatekeepers, participants can collaborate permissionlessly while preserving integrity, proving what the data is, where it came from, and that it has not been tampered with. This allows a system that enables “sharing,” while also dissolving silos, making coordination rational, enabling AI to compound faster by forging inter-company data collaboration work.

The community and contributors lie at the center of #DeCorp. The year has been all about you, and it will continue to be so for 2026! It's lovely to see a community-created artwork to summarize the past year. We wish everyone the best. Keep DeCorping!

It’s been a tremendous year for #DeCorp. This year, we built from the ground up, growing a strong base of data workers and trusted enterprise data clients. Thank you to everyone for your contributions and support. Wishing you all the best in the year ahead. Merry Christmas! 🎄

Traditional corporate structure runs from the top-down, with workers typically earning 10% of each dollar value they generate. At #DeCorp, contributors are equal with no management layers and intermediaries on top cutting the cake. Instead, the pipeline is managed by algorithms.

On the business-to-business side, Tagger solves a critical bottleneck in the AI data industry: lack of data trust. AI data are often even more prone to misuse, theft, and alterations than regular IPs. They form one of the largest branch of AI advancement, and yet, companies still work behind closed doors to prevent data leakage, spending millions each year to protect data. This is much simpler in #DeCorp, enabling an authenticated data management system that enables cross-company collaborations and traceable data management rights.

We are pleased to announce that $TAG will be listed on @Aster_DEX Spot. In conjunction with this listing, we are opening a trading competition with a total prize pool of $100,000 (split evenly between $ASTER and $TAG). Campaign Details Window Dec 5, 10:00 UTC to Dec 12, 23:59 UTC. Qualification Requirements To remain eligible for rewards, you must meet both criteria: Hold: Maintain a balance of 444 $ASTER (Spot + Perpetual) throughout the entire campaign window. Trade: Accumulate a minimum of $4,000 in trading volume on the TAG/USDT Spot pair. Prize Allocation Rewards are distributed pro-rata based on your share of total trading fees contributed during the event. Note: Rewards are capped at 3% of the total prize pool per user.

Data Passport governs permissions and authorization for data management and transfer. This enables safer and more efficient internal data management for companies while also opening the door for cross-company data collaboration (something that's almost never done in traditional corporate structure due to trust issues). AI trainers and data cleaners can be granted right to data access only while data are held by management layers in a company. Layered permissions with different rights can also be granted. Data passports can also be burnt, transferred in a trade, or even sold in a "usable but not visible" form. This forms a crucial B2B infrastructure for #DeCorp.

Become a part of the #DeCorp workforce at Tagger. Work when you want, from where you are, without gatekeepers deciding who is allowed to participate. #DeCorp scales by itself: tasks are labeled and reviewed through peer-to-peer consensus. Fair Work. Fair Pay. Fair Data. Fair AI.

Server maintenance has been completed. All data tasks and main site functions now resume. We thank you for your patience. Happy #DeCorp-ing!

We will be undergoing server maintenance starting 1PM UTC+0 today, expected to last roughly 4 hours. During that time, data tasks will be paused. We will notify promptly after the completion of server maintenance. Time to have a lunch break from #DeCorp :)