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Port3 Network: Building AI Social Data Infrastructure for the Web3 World
From Social Data to AI Brain: What Kind of AI Network Will Port3 Network Build for the Web3 World?
1. Introduction
In the world of Web3, data is transforming from static information into dynamic assets. In particular, user social behavior data is becoming the most valuable yet underdeveloped "digital mineral" in the AI era. The enormous value contained in the social data generated every minute is still not fully tapped into by people.
We see that the reality of Web3 is fragmented: on one hand, we have witnessed explosive growth of 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 unable to be truly accessed.
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 are all proposing the vision of "callable data + executable intentions."
Against this backdrop, a question emerges: If AI is the future, who will build the data layer and decision-making foundation of Web3? There is a project called Port3 Network that 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 on user behavior that is friendly to AI models. It not only integrates on-chain data with off-chain social behavior but also standardizes and recognizes intent, making the data an "action template" that agents can understand, call, 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" ahead of the true integration of narratives such as data sovereignty, on-chain identity, and social finance.
We will deeply analyze the product matrix, technological moat, token mechanism, and growth logic of Port3, discussing how it establishes a closed loop for data circulation aimed at AI Agents in the fragmented Web3 world, and becomes the hidden infrastructure of the next trillion-level 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 standardizing it with an AI engine, 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 financing.
August 2023: Secured a new round of millions of dollars in funding
October 2023: Announced 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 engaged in backend development at Tencent and Viabtc Technology Limited, with 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 the product matrix of Port3 includes several sub-modules such as SoQuest, Rankit, OpenBQL, and on.meme, which may seem scattered, 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 conversion."
3.1 Port3 Core Infrastructure
3.1.1 Data Aggregation - SoQuest
SoQuest is the core data gateway 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 trigger mechanism and collects user social behaviors as its target, bridging the behavioral pathways 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., creating one of the most comprehensive behavior collection systems in the Web3 field.
By mid-2025, Port3 Network had 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, constructing a real, multi-dimensional, and high-frequency Web3 social behavior database.
To enhance the platform's scalability and data collection capabilities, SoQuest has launched the QaaS(Quest-as-a-Service module, allowing project teams to integrate 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 integration 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 for Port3's full-chain behavioral asset closed loop and also the original source of the behavioral semantic data needed to support AI reasoning.
3.1.2 Data Deposition - AI Social Data Layer
The user behavior data captured by SoQuest ultimately resides in the core module of the Port3 Network------AI Social Data Layer, which is a structured behavioral database specifically designed for AI applications. It is also the underlying infrastructure for Port3 to achieve "behavioral 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 reasoning 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, and continuously updates in real-time through application modules such as SoQuest and Rankit, constructing a dynamically self-growing social data system. It is the behavioral cognitive hub of Port3, structuring and semantizing 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 of Rankit 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 discussion focus, 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 recently launched USD1 ecological data engine, which uses heat maps, social activity, and on-chain dynamics to track potential projects on the BNB Chain in real-time, becoming a smart compass for DeFi users to capture Alpha.
With the support of Rankit, Port3 can not only provide data but also "explanatory data"------not only 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 cortex of Port3, serving as the semantic core and operating 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 perform on-chain operations with instructions like "buy NFT on the Aptos chain," bridging EVM, BTC, and Solana multi-chain environments.
Standardized Execution Layer: Supports one-click automation of on-chain asset operations (such as trading, staking, and liquidity addition), serving 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 driving the creation 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 can 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 commands.
Applications include automated investment assistants, interactive robots, and blockchain game smart assistants, 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 space 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 behavioral 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 the Web3 AI narrative not primarily because of its advanced large model capabilities, but because it has built a highly valuable social behavior data asset with great 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. Tens of millions of on-chain and off-chain behavioral data accumulation
Relying on the three-year operation of the SoQuest task platform, Port3 has accumulated over 10 million user participation trajectories, covering multiple 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, forming an extremely dense social behavior map. In the current context of AI models where 'data is fuel', such structured and high-frequency interaction 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, with continuous real-time data updates.
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 timeliness of the data sources. Through the data channels co-built with project parties, Port3 continuously absorbs the latest ecological trends and user tendencies.