Data Mining: Real-Time Intelligence at Scale

&milo’s data mining system is a core component of our agentic architecture, enabling real-time on-chain monitoring, transaction analysis, and wallet intelligence. Unlike traditional blockchain data pipelines that store historical data and process it in bulk, &milo agents operate on-demand, opening and closing data streams dynamically to optimize both speed and efficiency.

On-Demand Data Streams for Agents

Each agent in &milo can initiate a data stream for a specific smart contract, transaction type, or wallet cluster. These streams operate in real-time, allowing the system to:

• Track transaction flow for a specific contract (e.g., a DEX pool, a lending protocol, or an NFT mint).

• Monitor wallet activity (e.g., tracking whales, insiders, or bot-driven behaviors).

• Analyze liquidity shifts (e.g., sudden inflows/outflows that could indicate manipulation).

To maintain efficiency, data streams are not permanently active. Instead, they are opened and closed dynamically based on need, ensuring that system resources are allocated to critical analysis in real time.

Distributed, High-Throughput Processing

&milo leverages a distributed node architecture that enables parallelized data mining at scale. Instead of relying on a single bottlenecked node, our high-throughput network allows agents to:

• Process vast amounts of blockchain data in parallel, increasing speed and reducing latency.

• Stream transactions in real-time, without waiting for traditional indexers to update.

• Dynamically adjust computing power, allocating resources based on workload demand.

By distributing workloads across multiple nodes, the system ensures scalability and efficiency, allowing agents to track and analyze data without overwhelming system resources.

Detecting Artificial Activity & Market Manipulation

&milo’s real-time data mining capabilities allow the system to detect abnormal patterns, helping users identify potential manipulation or inorganic activity. Some key detection capabilities include:

1. Artificial Trading Volume Detection

• Detect wash trading patterns where multiple small wallets trade back and forth to inflate volume.

• Identify transaction clustering, where trades occur between the same wallets repeatedly to simulate market activity.

2. Fake Holder Count Detection

• Identify SPL account farming, where multiple new wallets are created solely to inflate holder counts.

• Detect airdropped liquidity manipulation, where tokens are distributed widely to simulate organic adoption.

3. Liquidity & Risk Monitoring

• Track wallet migrations to detect early signs of rug pulls or protocol insolvency.

• Monitor liquidity movement patterns, ensuring that supply and demand remain natural.

Agentic Decision-Making Based on Data Mining

&milo’s data mining is fully integrated into agent decision-making, allowing agents to:

• React in real-time to market anomalies.

• Alert users when suspicious activity is detected.

• Automatically adjust execution strategies based on live blockchain data.

For example, if a DeFi Trade Agent detects artificial liquidity spikes, it may:

1. Request additional analysis from the Analyst Agent.

2. Avoid trading on manipulated pairs.

3. Adjust stop-loss settings dynamically to protect against sudden market reversals.

By integrating real-time data mining, distributed processing, and agent-driven decision-making, &milo creates a highly adaptive, intelligent system that continuously analyzes and responds to blockchain dynamics as they happen.