In the blockchain world, data inherently exists in raw form (raw logs) — chains of bytes, events, and states that are difficult for humans to read and almost 'indigestible' for AI. Chainbase is changing that. They not only organize data for easier human use but also build infrastructure that helps AI read and understand blockchain data naturally.

🧠 Manuscript Layer — Turning Raw Logs into Smart Tables

The Manuscript Layer is a real-time data co-processor that helps convert on-chain and off-chain logs into schema-rich relational datasets — meaning data with a clear structure, 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 like JSON, SQL, CSV, ORC, and can connect directly to storage like S3, MySQL.

Strength: instead of spending hours running a node, decoding logs, or building an ETL pipeline yourself, you can now simply define the transformation once and get AI-ready data — reducing the time from hours to just minutes.

🏗️ No ETL Needed — Just Describe What You Want

Traditionally, to get AI-ready data from blockchain, you had to:

  1. Run a node or rely on an RPC provider.

  2. Manually decode logs and events.

  3. Build an ETL pipeline to filter and normalize data.

With Manuscript, that chain of processes is replaced by a simpler approach:

  • Write a script as desired (in a familiar language).

  • The system runs and returns schema-rich data immediately.

  • AI can ingest without additional processing.

💡 Tokenizing Knowledge

The big difference: Manuscript is not just data infrastructure — it is also a knowledge marketplace.

Users can contribute:

  • Data processing scripts can be reused.

  • AI models have been trained from that data.

These assets can be tokenized as NFTs or modules and sell rights or earn rewards in 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: Machine-readable immediately, no manual parsing required.

  • Multi-language & 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 analytical dashboards.

🔮 The Future: Data Becomes a Liquid Economy

If previously blockchain data required many layers of intermediaries to extract, with Chainbase and Manuscript, data transforms itself into a format that AI can use directly. At that point:

  • AI agents can '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 arises:

  • Are you ready to write a Manuscript to feed your on-chain AI agent?

  • When knowledge can be traded like tokens, how will the data market explode?

♡𝐥𝐢𝐤𝐞💬 ➤ #Chainbase @Chainbase Official $C