From Social Data to AI Brain: How Port3 Network Constructs the AI Data Layer of Web3

1. Introduction

In the Web3 world, data is shifting from static information to dynamic assets. Users' social behavior data has become the most valuable yet underdeveloped "digital minerals" in the AI era. The social data generated every moment contains immense value that has not yet been fully mined.

The reality of Web3 is fragmented: on one hand, vertical protocols such as DeFi, NFT, and GameFi are experiencing explosive growth, generating a vast amount of behavioral data from users both on-chain and off-chain; on the other hand, this data is scattered across isolated DApps, transaction records, and social platforms, lacking structured integration, making it difficult to build a unified profile and also impossible to be truly utilized.

At the same time, the rise of AI is rapidly reshaping the entire digital world. OpenAI's ChatGPT, Anthropic's Claude, and Web3-based Agent projects such as Autonolas, Morphpad, and Mind Network are all proposing the vision of "callable data + executable intentions."

In this context, a question arises: If AI is the future, who will build the Data Layer and decision-making foundation of Web3? Port3 Network provides a rather ultimate answer:

From the initial SoQuest task platform, to the Rankit social behavior scoring engine, and then to the OpenBQL cross-chain intent execution language, Port3 has built a "social data infrastructure" centered around user behavior and friendly to AI models. It not only integrates on-chain data with off-chain social behavior but also standardizes and recognizes intents, transforming data into "action templates" that agents can understand, invoke, and execute.

In other words, Port3 is no longer a single task platform or tool, but has strategically occupied the position of "Web3 Data Brain" before the narratives of data sovereignty, on-chain identity, and social finance have truly integrated.

This article will deeply analyze the product matrix, technological moat, token mechanism, and growth logic of Port3, exploring how it establishes a data circulation closed loop for AI Agents in the fragmented Web3 world and becomes the hidden infrastructure of the next trillion-level trend.

2. Project Introduction

What is Port3 2.1?

Port3 Network is an AI-driven Web3 social data infrastructure project aimed at building a cross-chain, programmable, and callable social Data Layer. By aggregating user behavior data from Web2 and Web3, and standardizing the processing with an AI engine, Port3 has created a complete closed-loop system from data collection ( SoQuest ), structured scoring ( Rankit ), smart querying ( OpenBQL ) to agent invocation ( Ailliance.ai ), becoming a key facility for the assetization of on-chain behavior in the AI era.

Project Overview 2.2

2.2.1 Financing Situation

February 2023: Completed $3 million seed round financing

August 2023: Secured a new round of multi-million dollar financing

October 2023: Announced investment from DWF Labs, along with grant support from Binance Labs, Mask Network, and Aptos.

2.2.2 Team Situation

Max D.: Co-founder, with experience at Apple; possesses extensive experience in Web3 project incubation and ecosystem expansion.

Anthony Deng: Co-founder, previously engaged in backend development at Tencent and Viabtc Technology Limited, with many years of experience in high-concurrency system design and distributed architecture.

3. The Vision of Port3: From "Task Platform" to "AI Social Data Layer"

The product matrix of Port3 includes several sub-modules such as SoQuest, Rankit, OpenBQL, and on.meme. While they seem dispersed, they can actually be summarized into a core main line: "Behavior is an asset, and Port3 is responsible for the closed loop of data flow from collection to transformation."

3.1 Port3 Core Infrastructure

3.1.1 Data Aggregation - SoQuest

SoQuest is the core data entry built by Port3 Network, a Web3 user behavior capture platform that integrates task distribution, behavior verification, community growth, and data collection. Its essence is a data generation system that uses tasks as the triggering mechanism and user social behaviors as the collection target, bridging the behavioral paths between on-chain interactions and Web2 social platforms.

SoQuest supports mainstream Web2 platforms such as Twitter, Telegram, and Discord, and is compatible with interactions on 19 chains including EVM, Solana, Aptos, and Sui, including transactions, authorizations, NFT minting, etc., forming one of the most comprehensive behavior collection systems in the Web3 field.

By mid-2025, Port3 Network has collected dynamic data from over 6 million users and 7,000 projects, covering more than 10 million crypto users. This has generated a vast amount of user behavior records and on-chain social interaction events, creating a real, multi-dimensional, and high-frequency Web3 social behavior database.

To enhance the scalability and data collection capabilities of the platform, SoQuest has launched the QaaS( Quest-as-a-Service) module, allowing project parties to embed the task system into their own dApp or Telegram Mini App. In 2025, the verification API will be further opened, enabling the completion of verification logic embedding without the need for pre-set templates, significantly improving the standardization and universality of the task system.

SoQuest is not just a task platform; it is the starting point of Port3's full-chain behavioral asset closed loop and also the original source of the behavioral semantic data required for AI reasoning.

3.1.2 Data Accumulation - AI Social Data Layer

The user behavior data captured by SoQuest ultimately settles into the core module of the Port3 Network -- AI Social Data Layer, which is a structured behavior database specifically designed for AI applications. It is also the underlying facility for Port3 to achieve "behavioral assetization" and "information financialization (InfoFi)."

Unlike traditional on-chain data platforms ( such as The Graph, Dune, etc., which are designed with the goal of "querying", Port3's Data Layer focuses on: how to make data usable for AI models and support automated on-chain reasoning and interaction.

The AI Social Data Layer integrates tens of millions of on-chain interaction records and social task behavior data, continuously updated in real-time through application modules such as SoQuest and Rankit, creating a dynamically self-growing social data system. It serves as the behavioral cognitive hub of Port3, structuring and semantizing complex on-chain and off-chain behavioral data, providing agents with "understandable, combinable, and callable" data fuel.

![From Social Data to AI Brain: What kind of AI network will Port3 Network create for the Web3 world?])https://img-cdn.gateio.im/webp-social/moments-e99f6dd0ad2c1543a76148cd77b3d3a7.webp(

3.1.3 Data Application - Rankit + OpenBQL + Ailliance.ai → AI Agent System

Rankit: AI-driven social behavior analysis engine

Rankit is the flagship application of Port3's social data capabilities, serving as the "visual execution" of BQL data capabilities on the AI layer.

Rankit’s capabilities and paradigm innovation:

• Cross-platform social heat score: Integrates social signals from Twitter, Telegram, Discord, etc., to identify key trends, hot projects, and sentiment shifts in the Web3 world.

• Semantic Recognition and Scoring Modeling: Through NLP and large model sentiment analysis, the focus of discussion, KOL influence, and user trust levels will be transformed into structured indicators for community governance, lending risk control, on-chain transactions, and other scenarios.

• Vertical scenario landing demonstration: For example, the newly launched USD1 ecological data engine, which links heat maps, social activity, and on-chain dynamics to track potential projects on the BNB Chain in real-time, becomes an intelligent compass for DeFi users to capture Alpha.

With the support of Rankit, Port3 not only provides data but also offers "explanatory data"—not only telling you what happened but also telling you what to do.

![From Social Data to AI Brain: What kind of AI network will Port3 Network build for the Web3 world?])https://img-cdn.gateio.im/webp-social/moments-4f1158531e71cb17cde8a6d112be2680.webp(

OpenBQL: Intent-driven On-chain Execution Language

If SoQuest is the data entry, then BQL)Blockchain Quest Language( is the cerebral cortex of Port3, the semantic core and operational engine for processing, organizing, and invoking all behavioral data.

The Role and Mechanism of BQL:

• Universal Language Layer: BQL provides a natural language-friendly query structure, enabling developers or Agents to execute on-chain operations with commands like "buy NFT on the Aptos chain", bridging EVM, BTC, and Solana multi-chain environments.

• Standardized Execution Layer: Supports on-chain asset operations ) such as transactions, staking, and liquidity addition ( with one-click automation, serving as the key hub for on-chain behavior automation.

• Data Semantic Extractor: Provides standard structured data support for AI models and Agents, achieving high-frequency data updates and calculations required for information financialization ) InfoFi (.

With the help of BQL, Port3 is promoting the construction of a new "on-chain natural language protocol" in the Web3 world, elevating on-chain behavior from the "code layer" to the "intention layer"—machines not only execute the instructions you give but also understand your intentions.

AI Agent Integration Capability: Ailliance.ai

• Port3 is building a universal Agent API layer, allowing developers to directly call structured data generated by Rankit/SoQuest/OpenBQL or execute instructions.

• Applications include automated investment assistants, interactive robots, blockchain game smart assistants, etc., covering various scenarios such as trading decisions, task publishing, and community operations.

This entire product structure makes Port3 the only platform in the Web3 social data track that possesses the "full-process capability of 'collection → analysis → application → invocation'".

Its ultimate goal is to build a Web3 AI standard protocol network based on behavioral data as the underlying layer, enabling AI Agents to understand, recognize, and operate on-chain assets.

![From Social Data to AI Brain: What Kind of AI Network Will Port3 Network Build for the Web3 World?])https://img-cdn.gateio.im/webp-social/moments-4b8f5aae018584aeb3956b96e0c8303d.webp(

) 3.2 Port3's Moat: Growth Flywheel Driven by Business Accumulation

Port3 can take a leading position in Web3 AI narratives not primarily due to its advanced large model capabilities, but because it has built a high-value social behavior data asset with significant depth and breadth during its business accumulation process. This data advantage lays a unique foundation for Port3's AI applications, Agent construction, and model training.

3.2.1. Millions-level on-chain and off-chain behavioral data accumulation

Leveraging SoQuest's three-year task platform operation, Port3 has accumulated participation trajectories from over 10 million users, covering various dimensions such as task behavior, wallet interactions, on-chain assets, and community engagement. This data spans both Web2 and Web3, including Twitter posts, Discord activity, Telegram retention, on-chain transactions, staking, and holdings, creating an extremely dense social behavior graph. In the current context of AI models where "data is fuel", this type of structured and high-frequency interactive behavior data is undoubtedly the most valuable input resource for building Web3 AI Agents.

3.2.2 Deep cooperation with thousands of project parties, data continuously and real-time updated

Port3 is not a platform focused on a single product, but has established partnerships with over 7000+ Web3 projects, covering multiple scenarios such as airdrop issuance, task design, community governance, and on-chain interactions. This cooperation not only brings real user behavior but also ensures the diversity and timeliness of data sources. Through the data channels co-built with project parties, Port3 continuously absorbs the latest ecological trends and user trends, constructing a dynamically evolving data engine instead of a static snapshot. This data updating capability provides a continuously evolving "training material pool" for AI models.

3.2.3 Forming a dedicated dataset for AI model training to provide semantic support for on-chain Agents

Compared to general Web2 data, the on-chain identity, interaction paths, and asset behaviors of Web3 users exhibit high anonymity and structural complexity, making it difficult for traditional models to adapt. Port3, through Rankit's semantic recognition and behavior tagging system, has precisely opened up the mapping path between on-chain behavior and natural language semantics. For example: "Wallet A participates in an airdrop in Protocol B +"