From Social Data to AI Brain: What Kind of AI Network Will Port3 Network Create for the Web3 World?

1. Introduction

In the world of Web3, data is transforming from static information into dynamic assets. Users' social behavior data is becoming the most valuable yet underdeveloped "digital mines" in the AI era. The immense value contained in the social data generated every minute has yet to be fully tapped.

The reality of Web3 is fragmented: on one hand, we have witnessed explosive growth in vertical protocols such as DeFi, NFTs, and GameFi, resulting in a large amount of behavioral data generated by 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 impossible to be truly utilized.

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

Against this backdrop, a question arises: If AI is the future, then who will build the data layer and decision-making foundation for Web3? Port3 Network provides a rather definitive answer:

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

In other words, Port3 is no longer a singular task platform or tool, but has strategically occupied the position of "Web3 Data Brain" ahead of the true integration of narratives such as data sovereignty, on-chain identity, and social finance.

This article will delve into 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 for the next trillion-dollar trend.

2. Project Introduction

What is 2.1 Port3?

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 supplemented by an AI engine for standardized processing, Port3 has created a complete closed loop from data collection (SoQuest), structured scoring (Rankit), intelligent querying (OpenBQL) to agent invocation (Ailliance.ai), becoming a key facility for on-chain behavior assetization in the AI era.

Project Overview 2.2

2.2.1 Financing Situation

February 2023: Completed a $3 million seed round funding.

August 2023: Secured a new round of funding in the millions of dollars.

October 2023: Announced the acquisition of investment from DWF Labs, and received grant support from Binance Labs, Mask Network, and Aptos.

2.2.2 Team Situation

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

Anthony Deng: Co-founder, previously worked 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 Infrastructure"

Although Port3's product matrix includes several sub-modules such as SoQuest, Rankit, OpenBQL, and on.meme, which seem scattered, they can actually be summarized into a core mainline: "Behavior is an asset, and Port3 is responsible for the closed loop of data flow from collection to conversion."

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. Essentially, it is a data generation system that uses tasks as a triggering mechanism and captures user social behaviors as its 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 widely covered behavior collection systems in the Web3 field.

As of mid-2025, the 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 blockchain social interaction events, creating a real, multidimensional, and high-frequency Web3 social behavior database.

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

SoQuest is not just a task platform; it is the starting point of the Port3 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 converges into the core module of the Port3 Network - the AI Social Data Layer, which is a structured behavior database specifically designed for AI applications. It is also the underlying infrastructure for Port3 to achieve "behavior assetization" and "information financialization (InfoFi)."

Unlike traditional on-chain data platforms (such as The Graph, Dune, etc.) that are designed with the goal of "querying," Port3's data layer focuses on: how to make data usable for AI models and support on-chain inference and interaction that can be executed automatically.

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 semantically enriching complex on-chain and off-chain behavioral data to provide agents with "understandable, combinable, and callable" data fuel.

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 at the AI layer.

The capabilities and paradigm innovation of Rankit:

• Cross-platform social heat score: Integrates social signals from Twitter, Telegram, Discord, etc., to identify key trends, hot projects, and shifts in sentiment 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 are transformed into structured indicators for community governance, lending risk control, on-chain transactions, and other scenarios.

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

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

OpenBQL: Intent-driven on-chain execution language

If SoQuest is the data entry point, then BQL (Blockchain Quest Language) is the data cerebral cortex of Port3, serving as 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, allowing 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: A one-click automated processing that supports on-chain asset operations (such as trading, staking, liquidity adding) and serves as the key hub for the automation of on-chain activities.

• Data Semantic Extractor: Provides standard structured data support for AI models and Agents, enabling 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 actions from the "code layer" to the "intention layer"—machines not only execute the commands 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, community operations, and more.

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

The ultimate goal is to build a Web3 AI standard protocol network based on behavior data, enabling AI Agents to understand, recognize, and operate on-chain assets.

The Moat of Port3 3.2: The Growth Flywheel Driven by Business Accumulation

Port3 can take the lead in Web3 AI narratives, not primarily because of its advanced large model capabilities, but due to its accumulation of high-value social behavioral data assets with significant depth and breadth during its business development process. This data advantage lays a unique foundation for Port3's AI applications, Agent development, and model training:

3.2.1. Ten million level on-chain and off-chain behavior data accumulation

Leveraging SoQuest's three-year mission platform operation, Port3 has accumulated over 10 million levels of user participation trajectories, covering multiple dimensions such as task behavior, wallet interactions, on-chain assets, and community engagement. This data spans Web2 and Web3, including Twitter posts, Discord activity, Telegram retention, on-chain transactions, staking, and holdings, forming an extremely dense social behavior map. 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 In-depth cooperation with thousands of project parties, data continuously updated in real time.

Port3 is not a platform focused on a single product, but has established partnerships with over 7000+ Web3 projects, covering various scenarios such as airdrop issuance, task design, community governance, and on-chain interactions. This collaboration not only brings real user behavior but also ensures the diversity and real-time nature of data sources.