Chainbase & Manuscript Layer: AI-native Data Infrastructure for Blockchain

In the blockchain world, data inherently exists in raw form (raw logs) — these are byte strings, events, and states that are difficult for humans to read and almost "indigestible" for AI. Chainbase is changing that. They are not only organizing data to make it user-friendly, but also building infrastructure to help AI read and understand blockchain data naturally. 🧠 Manuscript Layer — Convert Raw Logs into Smart Tables Manuscript Layer is a real-time data co-processor that helps convert on-chain and off-chain logs into ( relational datasets ) with rich schema — that is, clearly structured data, foreign keys, easy to query, model, or train AI. Users can write "Manuscript" — data transformation scripts — in many popular languages such as Python, Rust, Go, WASM. The output can be in familiar formats such as JSON, SQL, CSV, ORC, and can connect directly to storage solutions like S3, MySQL. Strengths: instead of spending hours running nodes, decoding logs, or building an ETL pipeline from scratch, you only need to define the transformation once and immediately receive data ready for AI — reducing the time from hours to just a few minutes. 🏗️ No ETL Needed — Just Describe What You Want Traditionally, to have AI-ready data from blockchain, you must: Run a node or rely on an RPC provider. Decode logs and events manually. Build an ETL pipeline to filter and normalize data.

With Manuscript, that chain of processes is replaced by a simple approach: Write a script according to your wishes (in a familiar language).The system runs and returns schema-rich data immediately.AI can ingest without additional processing. 💡 Tokenization of Knowledge The big difference: Manuscript is not just a data infrastructure — it is also a knowledge marketplace.

Users can contribute: Reusable data processing script. The AI model has been trained on that data. These assets can be tokenized as NFTs or modules and sold for royalties or rewarded with token C.

This turns knowledge into liquid assets — where every line of code, every data pipeline has exchange value. 👀 Why Does This Change the Game? Schema-rich data: Readable right away, no manual parsing needed. Multilingual & modular: Developers in any stack can easily participate. Socialized infrastructure: Knowledge becomes a tradable asset. AI-native by design: Born for AI agents, not just for analytics dashboards. 🔮 The Future: Data Becomes the Liquid Economy If previously blockchain data required multiple layers of intermediaries to be mined, with Chainbase and Manuscript, the data transforms into a form that AI can directly utilize. At that point: AI agents can autonomously "read" the blockchain and respond in real-time. Developers and researchers can share & monetize data pipelines. A liquid knowledge ecosystem emerges — where data and intelligence are exchanged as digital assets. 💬 The question is: Are you ready to write a Manuscript to nurture your on-chain AI agent? When knowledge can be bought and sold like tokens, how will the data market explode? ♡𝐥𝐢𝐤𝐞💬 ➤ #Chainbase @ChainbaseHQ $C {spot}(CUSDT)