From social data to AI brains: What kind of AI network will Port3 Network build for the Web3 world?

1. Introduction

In the world of Web3, data is transitioning from static information to dynamic assets. Especially user social behavior data is becoming the most valuable yet underdeveloped "digital mineral" in the AI era. The immense value contained in the social data generated every minute and every second has not yet been fully explored.

We see that the reality of Web3 is fragmented: on one hand, we have witnessed explosive growth in vertical protocols such as DeFi, NFTs, and GameFi, with users generating a large amount of behavioral data 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 unable 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 are all proposing the vision of "callable data + executable intent."

Against this backdrop, a question emerges: If AI is the future, then who will build the data layer and decision-making foundation for Web3? There is a project called Port3 Network that provides a rather ultimate answer:

From the initial SoQuest task platform, to Rankit's social behavior scoring engine, and then to OpenBQL's 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, making data an "action template" that intelligent agents can understand, invoke, and execute.

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

Klein Labs will deeply analyze Port3's product matrix, technological moat, token mechanism, and growth logic, exploring how it establishes a data circulation closed loop aimed at AI Agents in the fragmented Web3 world, and becomes the secret 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 led by Jump Crypto, aimed at building a cross-chain, programmable, and callable social data layer. By aggregating user behavior data from Web2 and Web3, and employing an AI engine for standardized processing, Port3 has created a complete closed loop of data collection ( SoQuest ), structured scoring ( Rankit ), intelligent querying ( OpenBQL ) to Agent invocation ( Ailliance.ai ), becoming a key facility for the assetization of on-chain behaviors in the AI era.

2.2 Project Overview

2.1.1 Financing Status

February 2023: Completed a $3 million seed round financing, led by Jump Crypto, with other participants including SNZ, Block Infinity, Dragon Roark, ViaBTC, Cryptonite, Lapin Digital, Cogitent, and Momentum6.

August 2023: Secured a new round of millions of dollars in financing, with investors including EMURGO, Adaverse Accelerator, and Gate Labs.

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

2.1.2 Team Situation

Max D.: Co-founder with work experience 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 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 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. Essentially, it is a data generation system triggered by tasks and focused on capturing user social behaviors, 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., forming one of the most widely covered behavior collection systems in the Web3 field.

As of 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 blockchain social interaction events, creating a real, multidimensional, 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 parties to embed the task system into their own dApp or Telegram Mini App. In 2025, the validation API will be further opened, enabling the completion of validation logic embedding without preset templates, greatly improving the standardization and versatility 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 behavioral 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 and Dune, which 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 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, building a dynamically growing social data system. It serves as the behavior cognition hub of Port3, structuring and semantically interpreting complex on-chain and off-chain behavior data, providing 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 and is 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 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 scenarios such as community governance, lending risk control, and on-chain transactions.

• Vertical scenario landing demonstration: For example, the newly launched USD1 ecological data engine, which tracks potential projects on the BNB Chain in real time through heat maps, social activity, and on-chain momentum, becoming 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-e99f6dd0ad2c1543a76148cd77b3d3a7.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, serving as the semantic core and operational engine for the processing, organization, and invocation of 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 using 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 trading, staking, and liquidity addition ( with one-click automation processing, which is the key hub for on-chain behavior automation.

• Data Semantic Extractor: Provides standard structured data support for AI models and Agents, achieving the 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, allowing on-chain actions to rise from the "code layer" to the "intention layer" ------ machines can 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 commands.

• Applications include automated investment assistants, interactive robots, 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 track that possesses the full process capability of "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.

![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-4f1158531e71cb17cde8a6d112be2680.webp(

) 3.2 Port3's moat: the growth flywheel brought by business accumulation

Port3 can take a leading position in Web3 AI narrative not primarily because it possesses advanced large model capabilities, but due to the highly in-depth and broad high-value social behavior data assets it has built 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. Accumulation of On-chain and Off-chain Behavioral Data at the Million Level

Leveraging SoQuest's three years of task platform operations, Port3 has accumulated over 10 million levels of user participation trajectories, covering multiple dimensions such as task behaviors, wallet interactions, on-chain assets, and community engagement. This data spans across 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 Deep 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 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 the data sources. By co-constructing data channels with project parties, Port3 continuously absorbs the latest ecological trends and user behaviors, building a dynamically evolving data engine rather than a static snapshot. This capability for data updates 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,