Join the waitlist to get early access to the Terminal 3 Network, launching in 2025.
The Terminal 3 Network (T3N) is a decentralized private data network that empowers individuals with self-sovereign control of their personal data, enabling verifiable private identities, secure AI agent interactions, and a trusted data economy. The network’s development is composed of three sequential phases, with each phase building on the previous one to achieve specific goals:
  • Phase 1: Decentralized private data - Ensure safe and private AI agents.
  • Phase 2: Proof of human and AI agent data layer - Establish a trusted oracle for verified humans and AI data.
  • Phase 3: Trusted data economy - Enable users to monetize their verified data securely and fairly.

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Users

The players in the T3N ecosystem are as follows:
  • Developers - Developers who build AI agent applications.
  • Data owners - Owners of private user data.
  • Data providers -Data providers are the entities that supply user data into the decentralized user data vault. Data providers are typically data owners themselves; however, they can also be any third parties granted consent by data owners.
  • Data consumers -Data consumers are the entities that utilize user data from the decentralized user data vault. These consumers are typically required to compensate data owners for accessing their data.
  • Node operators -Node operators maintain the infrastructure of the decentralized user data vault.
  • Compliance authorities - Compliance authorities are entities tasked with ensuring that organizations adhere to relevant laws, regulations, and industry standards. These authorities typically include both government-established regulatory agencies and industry-specific bodies.
  • Verifiable credential (VC) issuers - Verifiable credential issuers are entities that issue digital credentials that can be verified independently.
  • VC verifiers - VC verifiers are entities that validate and verify the authenticity and trustworthiness of VCs.

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Phase 1: Decentralized Private Data

Goal: Ensure data privacy and security when using AI agents Primary users
  • Developers (and applications)
  • Data owners
Use cases Data owners can safely automate transactional tasks with AI agents, such as:
  • Online financial product applications (credit cards, personal loans)
  • Insurance claim management
  • Customer support interactions
  • Job searching tasks
  • Patient registration
  • Online shopping
The Terminal 3 Network functions as a private data layer between consumer applications (e.g. AI agents) and an ecosystem of third-party integrations that require user data (e.g., booking.com) to complete transactions. At a high-level, the network:
  • Securely stores user data encrypted in a decentralized manner;
  • Provides access to private user data via privacy-enhancing technologies (PET); and
  • Delivers user data to third-party integrations (i.e. last mile data delivery) where only the intended recipient can view the data without the ability to link it back to anonymous identities.
Data owners can interact with the network in two ways: either indirectly through an AI agent or application, or directly through a user interface (UI).

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Interacting through an AI agent

AI agents, such as computer-using agents (CUA), are often used to automate specific tasks for their human operators. For instance, AI travel agents can make flight and bookings, while AI crypto trading agents can execute trades. T3N assists these AI agents in connecting with an ecosystem of third-party integrations via API or smart contracts, and conducting last mile delivery of private data necessary to complete transactions. This ensures that AI agents never have access to sensitive information, such as PII, API keys, or private keys. Other key highlights include:
  • T3N does not interact with data owners directly.
  • Data owners may be onboarded during the process if they do not yet have a T3 account
  • T3N performs critical verifications:
    • Requests are from authorized agents
    • Safe URL (i.e. whitelisted or user approved URL)
    • Fund amount (if there is any via Secure API)
  • All transactions and API calls are recorded and auditable.
Interacting with T3N through Agents

Figure 1. Data owners indirectly interact with T3N through an application, such as AI agents.

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Interact directly

Data owners can directly interact with T3N to manage data through a user interface to enrich their user data and manage their data token for future data consumption (Figure 2). A data token is a user-signed data access token that grants specific permission to disclose selective user data to the token holder. The data token can be single- or multi-use, and is non-transferable. This direct interaction with T3N allows data owners to enrich their data and properly configure their data tokens in advance, enabling them to take full advantage of automation when interacting with an AI agent.
Interacting with T3N directly

Figure 2. Data owners directly interact with T3N to manage data through a user interface.

T3N abstracts away all the complexities of managing and handling private user data for AI agent developers. This significantly helps accelerate time to market, gain trust from users, and quick access to a large user base. As for data owners, T3N provides peace of mind when using AI agents to enhance their life and better user experience for managing their identity and user data.

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Phase 2: Proof of Human and AI Agent Data Layer

Goal: Establish a trusted oracle for verified human and AI data. Primary users
  • Verifiable credential (VC) issuers
  • VC verifiers
  • Data owners
  • Compliance authorities
Use cases Reusable verified user data, such as:
  • Reusable KYC information
  • Proof of accredited investor qualification
  • Academic degrees and professional licenses
  • Loyalty program membership
  • Vaccination records
In Phase 2, T3N will evolve from a Decentralized Private Data Layer, where use cases primarily involve interactions between applications/AI agents and data owners, into a Proof of Human and AI Agent Data Layer, where verified user data can be reused with multiple third parties in a compliant manner. This significantly improves data interoperability for data owners, while enabling VC verifiers (e.g., banks) to reduce costs and liability associated with storing and verifying users’ credentials. Oftentimes, data owners are required to provide verified data (e.g., KYC info) each time they interact with different third parties, both physically and digitally (e.g., banks or telecom service providers). For example, when a user opens an account at Bank A, the bank needs to verify their KYC info. If the user then goes to Bank B, he needs to go through a similar KYC process again. This process is very time consuming and costly. In Phase 2, T3N will support the issuance and verification of W3C standard verifiable credentials to prove the trustworthiness of user data. W3C verifiable credentials establish a chain of trust through digitally signed attestations. A trusted issuer — a reputable and verifiable organization — attests to specific user claims within the credential. Relying parties can cryptographically verify the issuer’s signature to ensure the accuracy and integrity of these claims. This decentralized and cryptographically-secured method significantly improves the trustworthiness of user data compared to traditional approaches, and simplifies the reuse of verified user data. Data owners can grant or revoke data consumer access to their verified data, allowing for its reuse. For example, verified KYC info at Bank A can be reused at Telecom B. This eliminates the need for data owners to manage multiple KYC copies across various centralized systems. It also removes the burden on data consumers (e.g., enterprises) to assume liability for storing sensitive user data. In addition, T3N will support compliance authorities (e.g., a government enforcement agency) audits with logs associated with any suspicious data owner or retrieve user data within their legal jurisdiction in the event of suspicious activity. This is a conscious design choice, enabling users to benefit from a wider range of applications and conveniences that require regulatory compliance. However, the data owner would be notified if a compliance authority accessed his data in the event of an enforcement action.

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Phase 3: Trusted Data Economy

Goal: Enable users to monetize their verified data securely and fairly Primary users
  • Data owners
  • Data providers
  • Data consumers
Use cases
  • Data monetization
Data consumers and VC verifiers are the external economic sources for the ecosystem. Phase 3 will begin once T3N has enough quality user profiles to attract data consumers. These data consumers, such as advertisers, enterprises, or research organizations, will then compensate data owners for access to their data. This data can be used for targeted advertising, reusable credentials, clinical research, or AI training, etc. The diagram below (Figure 3) briefly describes how the economic model works:
T3N economic model

Figure 3. T3N economic model

Phase 1: Decentralized Private Data (aka Data Population)
  1. Data owners pay AI agent builders for personalized AI services.
  2. AI agent builders, on behalf of data owners, pay node operators for data storage and processing.
  3. Data owners pay node operators directly for data storage and processing.
  4. Data owners pay data providers for their data population services.
  5. Data providers, on behalf of data owners, pay node operators for data storage and processing.
Phase 2: Proof of Humanity and AI Agent Data Layer (aka Data Verification)
  1. VC issuers pay node operators for VC storage and processing.
  2. Data owners pay VC issuers for VC issuance.
  3. VC verifiers pay VC issuers for VC verification.
Phase 3: Trusted Data Economy
  1. Data consumers pay data owners for accessing their data.
NOTE: This is not an exhaustive list. In Phase 3, T3N will accelerate the shift towards a future where individuals own and control their identity and data. This will create a more equitable digital future, with equal rights and protections for both users and enterprises. User identity and data will no longer be scattered across various big tech companies, eliminating intermediaries who extract value from private and valuable user data.