The hottest topic right now is AI Agent, which occasionally brings forth billion-level projects. This is recognized not only in the cryptocurrency space but across society as well; AI Agent is seen as the next trillion-level opportunity.

This is because, once large models reach the level of human experts in various capabilities, practical applications become the primary direction. In the past, all industries had to be re-done with the internet. Now, all industries should be re-done with AI Agent.

AI Agent can automatically extract data from external sources without human intervention, make judgments through its own model, and then take action. In this logic, AI models like Claude, OpenAI, and Gemini are already performing very well. Therefore, the acquisition of external data will become an extremely important part, and with the massive emergence of AI Agents in the cryptocurrency space, the demand for high-quality on-chain data will also become enormous.

Chainbase @ChainbaseHQ is building the world's largest full-chain data network in the AGI era. Its mission is to make data easily accessible and usable, aiming to fundamentally change the collaboration between cryptocurrency and AI. Anyone can join and contribute to the network, and its token economy incentivizes every role within the network.

On-chain data appears to be accessible to everyone, but in reality, it is not that easy. On-chain data needs to be decoded from Raw data into Decoded data and Abstracted data. Moreover, there are currently a vast number of public chains, each with its own data format and completely different camps, such as BTC series, EVM series, Move series, Solana series, etc. Additionally, the volume of transactions processed by public chains daily is enormous, so to be easily accessible by AI, a processing layer like Chainbase network is necessary.

In the Chainbase ecosystem, on-chain data can be tagged, classified, and processed, transforming complex data into forms that are easy to understand and use. AI algorithms can automatically analyze massive blockchain data, uncover hidden patterns, trends, and anomalies, helping users gain insights from the data.

Chainbase's current data is also impressive, supporting over 200 public chains, with a total of over 30K registered developers, more than 27K projects created by developers, 600 million API calls daily, and daily query volume exceeding 3000TB.

At the same time, Chainbase has already partnered with many excellent AI projects, including Google Gemini & Google Cloud, Gaia, http://io.net, and GAIB, providing real-time access and processing of on-chain data for AI. This integration allows AI agents to utilize cryptocurrency data to provide personalized insights and automate workflows, ensuring a secure and reliable privacy-protected environment for data.

Chainbase Architecture

Chainbase has built a comprehensive data infrastructure based on a four-layer architecture and dual-chain system.

● Co-processor Layer: Just like the vast databases of Dune that are provided and supported by the community, the co-processor layer promotes the generation of high-quality data under open standards. Developers and data scientists process raw data and extract greater value by writing programs called "Manuscripts."

● Execution Layer: Achieves data parallelism and task parallelism, efficiently processing and storing large-scale data. It also introduces Eigenlayer to provide security guarantees.

● Consensus Layer: Uses CometBFT to ensure that the system can efficiently and robustly reach consensus under huge data loads.

● Data Accessibility Layer: On-chain and off-chain data can be integrated into Chainbase's decentralized data lake in a trustless manner. Advanced technologies such as Zero-Knowledge Proofs (ZKP) and Storage-based Consensus Paradigms (SCP) ensure the integrity and reliability of the data.

Manuscript

As a data platform, Manuscript holds a very core position in Chainbase. It is the primary tool for developers to create and publish data. It allows developers to seamlessly integrate on-chain and off-chain data into target data storage, making it easy to query and analyze. Manuscript provides a wealth of tools and resources for this process, making data processing more efficient and transparent. Through these technological means, Manuscript not only makes the acquisition of on-chain data more flexible and free but also greatly enhances the value of the data, allowing more people to easily use and apply this on-chain data.

Manuscript's data support is very comprehensive. Firstly, it supports interaction with data using any mainstream programming language, including Rust, Python, Node.js, Golang, etc. It supports various forms of data access, including SQL, DataFrames, HTTPS, gRPC, etc.

It supports chain interoperability. We know that there are currently a vast number of public chains, with more than a dozen commonly used ones. Manuscript achieves seamless integration of data from different blockchains by providing a unified interface and data processing methods, greatly improving the development efficiency and feasibility of cross-chain applications.

In summary, Chainbase will be an important infrastructure in the future AGI era, redefining Web3 data infrastructure using blockchain-native methods. It has built a four-layer dual-consensus network to achieve high accessibility across countless blockchains (data access), ensure data integrity in decentralized networks, and standardize data formats (data patterns). Additionally, we have introduced on-chain native AI capabilities, providing new possibilities for data analysis and applications.

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