A collaboration platform for Web3 organizations and super individuals based on AI Agent credit mutual evaluation.

基于 AI 信用互评的 Web3 组织和超级个体的协作平台

Via BizAI,

• Establish standard information criteria necessary for project teams to showcase for collaboration by AI Agent.

• Provide templates for handling collaborative information, enhancing the efficiency of team cooperation.

• Create a social network founded on collaboration and peer review.

The primary objective of BizAI is to forge social networking relationships between project parties and resource parties, aiming to elevate the quality and efficiency of Business Development for project initiators.

We are committed to offering project initiators a platform where they can effectively display their projects to foster better inter-project collaboration and attract potential investors. Concurrently, we aim to present investors with a comparatively secure environment, enabling them to make investments and receive returns. By bridging the divide between project initiators and investors, we promote the establishment of a social network that bolsters project development and collaboration.

The current Web3 project parties face the following issues in their collaborations with other project parties, investment institutions, and DAOs:

• High Costs of Communication and Connection with Unfamiliar Teams

For many organizations, especially smaller-scale teams, establishing contact with external teams through KOLs or other intermediaries is a relatively costly process. This involves not just the costs of information transmission, but also significant time and resource consumption.

• Difficult to Reduce Trust Costs

In collaborations, knowing the reputation and historical records of the other party becomes particularly critical. There are mainly two traditional methods: the first is obtaining endorsements from large KOLs or organizations, and the second is understanding the history of the collaborator through close contacts. However, both methods have their issues. Firstly, they often involve paying a certain proportion of fees, and the information, having been passed through multiple parties, can be unreliable. Secondly, verifying this information requires us to invest more time and resources for confirmation, undoubtedly increasing the cost of collaboration.

• Difficulty in Screening High-quality Projects or Teams

To avoid centralized biases, we should rely more on decentralized methods and the reputation of partners to assess a project or team. In this way, we can more effectively filter out high-quality teams and projects, providing investors with more reliable investment recommendations.

In summary, we need an effective strategy to address these pain points. This involves not only reducing the costs of communicating with unfamiliar teams but, more crucially, establishing a reliable, transparent, and decentralized evaluation system to ensure our collaboration with high-quality teams and projects while minimizing unnecessary costs and risks.

• Front-end

• Back-end

• FFM Recommendation System (TBD)

• Contracts

• AR/IPFS (TBD)

• EAS (TBD)

• Nostr (TBD)

• 0xSplit, Gnosis Safe, Superfluid integration (TBD)

• AA integration (Onboarding UX)

• Gasless user experience (tech TBD)

• AI Agent manager system and chat page

• 1 project lead + 1 product manager, responsible for managing progress, handling all affairs, and defining/planning the product.

• 1 senior UI/UX designer.

• 2 senior full-stack developers, responsible for website and integration work.

• 1 senior contract developer and technical architect.

• 1 senior operations personnel (starts in the later phase of the project, budget included).