What is PIN AI? Interpretation of PIN AI financing, application, protocol economy, architecture

What is PIN AI? How is PIN AI financing? How does PIN AI revolutionize data privacy? Learn how PIN AI solves the problem of digital identity fragmentation and provides truly personalized AI services through its decentralized architecture. Explore the advantages of secure edge computing and trusted execution environments (TEEs) in data privacy. Below, the editor of Script Home will introduce you in detail what PIN AI is? and PIN AI financing situation. Friends in need, let’s take a look!

In today's digital world, personal data is scattered on the platforms of major technology giants, making it difficult for users to control their data. Current AI applications, such as ChatGPT and Google Gemini, cannot provide truly personalized services due to the centralized data storage, and also raise privacy issues and hinder the implementation of customized experiences.

PIN AI solves these challenges by providing decentralized local personal intelligence systems, secure edge computing, and trusted execution environments (TEEs). This approach ensures that personal data is always private, while enabling seamless matching of AI agents with user needs. With these technologies, PIN AI empowers users to control their data and fully unleash the potential of AI.

What is PIN AI?

Personal Intelligence Network AI (PIN AI) is an open platform for personal AI that enables users to control their data and train and deploy AI models that meet their personal needs. PIN AI combines local computing, trusted execution environment (TEE) security and blockchain verification to enable seamless interaction between humans and AI agents, all of which are driven by personal AI. The platform connects users to a marketplace of professional AI agents that perform tasks such as appointment scheduling, data analysis, financial management, etc. while ensuring privacy and security.

Main features and advantages

• Decentralized local intelligence: AI models are trained and deployed directly on user devices to ensure privacy and security.
• Secure edge computing: Local data processing reduces the risk of data breaches and ensures sensitive information does not leave user equipment.
• Trusted Execution Environment (TEE): TEE provides an isolated and secure computing environment within the device, protecting data and AI interactions from external threats.
• Data ownership: Users have full control over their personal data and can manage, share and cash out by themselves.
• Agent Economy: An AI agent market focused on different tasks, including appointment scheduling, data analysis and financial management.

PIN AI Operations Area

Personal AI

PIN AI is centered on personal AI, allowing users to have AI models tailored to their needs and preferences. Unlike traditional AI systems that rely on centralized servers to run, individual AI models are trained and deployed directly on user devices. This ensures that AI provides personalized assistance in a private and secure environment.

Data ownership

Data ownership is one of the core principles of PIN AI. In the current digital environment, users’ personal data is often controlled by large tech companies, limiting their ability to manage and utilize their own data. PIN AI solves this problem by giving users complete control over their own data. Users can decide which data to share, with whom and under what conditions. This not only enables users to monetize data while ensuring privacy and security, but also enhances the autonomy of personal data.

Agency economy

PIN AI introduces the concept of Agent Economy, allowing professional AI agents to perform various tasks for users. These AI agents can make appointments, data analysis, financial management, and simplify daily digital tasks. The agency economy is a market where users can access and deploy different AI agents according to their own needs.

PIN AI Architecture

PIN Onchain Protocol

The PIN Onchain protocol uses blockchain technology through a series of smart contracts to ensure the integrity and security of data processing and AI proxy interactions, realizing on-chain verification and verification processes. The core of the agreement includes:

Verified Computing Framework: Verified Computing Framework is responsible for ensuring the accuracy and reliability of off-chain computing. It achieves this by verifying Trusted Execution Environment (TEE) certification reports and monitoring the activity of decentralized services including God Models, data connectors, and local large language model LLMs. This framework ensures that all computing and interactions are transparent and tamper-proof.

Agent Registration: Agent Registration is a decentralized registration system for AI agents and data services in the PIN AI network. It maintains a complete list of AI agents and comes with a reputation score and a staking mechanism. Users can discover and deploy appropriate AI agents based on the performance and reliability of AI agents, thereby building a trust and responsibility system within the ecosystem.

PIN on-chain verification

The PIN Onchain protocol supports on-chain verification of TEE authentication reports, ensuring that only verified secure calculations are performed. The verification process involves checking the integrity of the node and its execution of the calculations. In addition, the protocol will verify the zk proof generated by the AI ​​agent after performing tasks, further enhancing the security and transparency of AI interactions. To ensure that the nodes within the network are stable, efficient and interconnected, the PIN Onchain protocol includes a mechanism to monitor the activity of work nodes, thereby maintaining the healthy operation of the entire network and ensuring that users obtain reliable and efficient AI services.

Personal AI (Personal AI) protocol

Data Connector

Data connectors are software components that securely acquire, process and construct personal data within a trusted execution environment (TEE). They allow users to connect and retrieve information from major Web2 and Web3 platforms such as Google, Apple, Meta, Amazon, MetaMask, and Phantom, while ensuring data privacy and user control. Data connectors process and structure data into personal knowledge graphs, making it accessible and optimized for Personal AI.

How the data connector works

After the user authorization, the data connector securely accesses user data through the API and processes it as a personalized knowledge graph. It then submits a hardware-based authentication report to the PIN Onchain protocol to verify the security processing capabilities of the Trusted Execution Environment (TEE) node. Verified data will be stored securely according to user preferences (local device, cloud or dedicated storage) to protect privacy and enable direct AI access.

Local LLM (Personal AI)

Local large language models (LLMs) run directly on user devices (such as smartphones, laptops, or private clouds), ensuring sensitive data is always controlled by the user and ensuring privacy through localized processing. Core features include: context personalization based on the continuous update of user interaction, history and preferences to provide highly customized AI feedback; adopting a hybrid architecture that combines local computing with cloud resources when users allow; using trusted hardware isolation (TEE) for secure data processing to prevent unauthorized access; having iterative learning capabilities, so that the model is continuously optimized as user needs change.

How does local LLM work

The model is stored in compressed form on SSD/HDD or private cloud and accessed through PIN AI applications. AI computing is performed directly on the device CPU or GPU, ensuring sensitive operations remain local for security and privacy. The hybrid architecture allows users to enable cloud resources when needed to handle complex tasks while maintaining control over data for seamless scaling. Local personalization is achieved through offline learning and model updates, allowing AI to continuously adapt to user behavior and needs without affecting data privacy.

God Models

The data guardian (God) model is a dedicated verification model that runs in the PIN AI network trusted execution environment (TEE). They continuously evaluate Personal AI to ensure the accuracy and consistency of AI feedback with user data, while providing feedback to users through data connector integration, optimizing Personal AI development. God Models has built a powerful AI proxy ecosystem, supports iterative optimization of Personal AI, and actively detects and prevents threats such as data manipulation, adversarial behavior and synthetic data injection to ensure the integrity of the system.

God Models Evaluation Framework

• Initialization: Personal AI records basic metadata, including validated data sources, interaction history, and activity patterns.

• Periodic or random query: God Model evaluates the effectiveness of Personal AI in providing user-specific context information.

• Response Verification: God Model compares AI responses to the verified data log or previously stored status to evaluate its accuracy.

• Rating Adjustment: God Model assigns “knowledge scores” based on response content and adjusts based on consistency, time accuracy, and confidence levels.

Intent Match Protocol

Intent matching protocols are an important part of the PIN AI platform, aiming to achieve seamless coordination between user Personal AI and external AI agents. This protocol ensures efficient, privacy-protected and verifiable service execution by allowing users to express intent (i.e., AI-driven operations or service requests) and allows AI agents to compete for the best execution solutions.

Key components of intent matching protocols

• Intent Submission: Users submit structured intent requests through Personal AI, which contain parameters such as service category, budget and constraints.

• Bidding Submission: The AI ​​agent submits bidding information based on the user's intent request, including detailed content such as service capabilities, pricing, and reputation scores. The bidding process enables AI agents to demonstrate their own strengths and qualifications, ensuring that users receive high-quality services.

• Intent matching algorithm: The protocol uses intent matching algorithm to evaluate the bidding status of AI agents based on factors such as preference embedding, bidding competitiveness and credibility. This algorithm ensures that selected AI agents can provide services at the best quality and lowest cost.

Agent Service Agreement

Agent Service Agreement is a decentralized market that connects users' Personal AI with professional AI agents. The protocol promotes an open competitive economy of intent matching, transparent service execution and programmable payments, and promotes an innovative AI agent.

Key components of proxy service agreements

• Agent Service Economy: Supports micropayments, programmable payments, shared ownership stakes and on-chain reputation tracking, ensuring transparent and efficient transactions, and allowing AI agents to receive fair compensation. Users can pay by task or automatically perform periodic payments, and the shared ownership mechanism encourages collaboration, while the reputation system helps users choose reliable AI agents.
• Agent Communication Protocol: Secure interaction between users and AI agents isolate sensitive data through Trusted Execution Environments (TEEs) and ensures the validity of results using on-chain verification. This mechanism protects privacy, prevents unauthorized access, and provides transparent and traceable service delivery.

Trusted Execution Environment (TEE)

Trusted Execution Environments (TEEs) are isolated areas within a processor or data center where programs can run without being disturbed by other parts of the system. These environments protect sensitive data and authenticate and authenticate the computations performed therein. Even if the main system is compromised, data and processes within TEE remain secure.

TEE Services

Trusted Execution Environment (TEE) provides a secure, isolated computing environment in PIN AI networks for performing sensitive tasks and ensuring confidentiality and integrity. These nodes can be customized by participants to support a wide range of workloads and application scenarios while maintaining strict security standards. Its core services include hosting data connectors in trusted environments to securely acquire and process user data, ensuring privacy throughout the process. Additionally, TEE performs private LLM inference and other privacy-protected calculations that are critical to PIN networks, enabling sensitive AI tasks to run in a trusted, tamper-proof environment. This architecture ensures that key processes from data processing to advanced model reasoning can be performed safely and transparently under the control of users, maintaining the highest level of data protection and operational reliability standards.

TEE Device Verification

Verification of TEE devices is an important step in establishing a trust-minimizing environment on the PIN network. This process involves verifying the hardware integrity of a TEE device (such as an Intel SGX device), ensuring that the CPU is an officially certified real device, and checking the validity and trusted source of the certificate chain. Before TEE executes any program, the Remote Attestation process ensures that the TEE runs untampered expected code, providing security at the hardware level. Data Connectors record verification details as on-chain metadata for transparency and auditability. This verification process applies to security reviews when registering TEE devices on the network.

TEE Task Verification

TEE Task Verification ensures that tasks performed by TEE nodes are correctly verified and penalized in the event of failure. The process includes the following steps:

• Submit proof: The TEE node submits its proof of work to the PIN Onchain verifier.

• Verification: The verifier checks whether the submitted proof is valid and confirms that the task is completed correctly.

• Accountability mechanism: If the task fails to pass the verification, the TEE node will be punished and its pledged funds will be deducted.

PIN protocol economy

The PIN protocol is the core support of the open source ecosystem built around PIN AI. It provides trustworthy activity tracking and exchange of value, access to valuable personal data, and provides an open and innovative platform for new AI services. This protocol ensures the integrity and security of data interactions within the PIN AI network, promoting a strong and transparent ecosystem.

How to start the PIN protocol economy

The core bilateral market of PIN connects user/personal AI with external AI, and the value of service continues to grow as users share more contextual data. The Proof of Engagement (PoE) protocol incentivizes participation through two components:

• Data connection incentive: Users link data to the network through encryption, thereby obtaining rewards. Use zkTLS, ML analysis of digital behavior, and digital IDs (such as WorldID) to prevent witch attacks.
• Valuable transaction proof: The user obtains the allocation quota by completing transactions involving economic value (cryptocurrency/fiat currency), which can be verified on the chain (such as zkTLS is suitable for fiat currency transactions).

The system drives engagement growth through reward data sharing and verifiable high-value interactions.

Key players in the PIN ecosystem

• End users: They are motivated to connect personal data to the PIN network while maintaining data ownership and privacy through data connectors. Their data provides the rich context needed to operate effectively for proxy services.

• Data Connectors: They are part of the PIN network infrastructure and are operated by third parties. The pledge and punishment mechanism is adopted to ensure security, and operators and pledgers are rewarded for their contributions.

• Agent Services: New Agent Services can be easily deployed through Agent Links. These agents utilize user context data to better respond to user intentions and provide valuable services. Agent service operators ensure security and receive incentives through crypto-economic mechanisms.

PIN AI Application

PIN AI launched its privacy-focused app on February 13, 2025, providing a customizable AI experience that runs directly on smartphones, based on open source models such as DeepSeek and Llama. The app supports iOS and Android, aggregates personal data from platforms such as Google or financial services to a secure "data bank" and provides personalized insights through features such as "GOD Score" (measures AI comprehension) and "Ask PIN AI" (for tasks such as travel planning). The application processes data on the device side while combining it with a private network to maintain efficiency and privacy protection.

PIN AI's business model charges extremely low fees for third-party AI to access user data (requires explicit authorization from the user), similar to Ethereum's Gas fee. The launch of the app was first aimed at early Android users (such as Discord members), then logged in to iOS, and went through the invitation-based testing phase before the full public beta.

PIN AI Financing History

PIN AI has successfully received significant financing to support its mission to build a decentralized, personalized AI platform. Its financing history has received strategic investment from well-known venture capital companies and angel investors. In September 2024, PIN AI completed a $10 million Pre-Seed round led by well-known venture capital firm Andreessen Horowitz (a16z), which has extensive experience in supporting innovative technology startups. Other well-known investors include Hack VC, Foresight Ventures, as well as angel investors Illia Polosukhin and Scott Moore.

in conclusion

PIN AI solves data fragmentation and privacy issues through decentralized device-side personal intelligence systems, secure edge computing and trusted execution environments (TEEs). This innovative approach allows users to regain control of their data while enjoying a personalized AI interactive experience. PIN AI’s Personal AI Protocol, Intent Matching Protocol and Agent Services Protocol jointly build a dynamic AI ecosystem that enhances data ownership and privacy protection.

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