Multi-Condition Data Retrieval

Accessing relevant Web3 data often requires navigating multiple platforms, applying rigid filters, and manually aggregating insights. NeulinkAI eliminates these inefficiencies by enabling users to retrieve complex, multi-variable data through natural language queries. No coding, no fragmented workflows.

How It Works

NeulinkAI leverages Natural Language Processing (NLP) and a Multi-Agent System to process advanced data requests seamlessly. Instead of manually filtering data across multiple sources, users can articulate complex conditions in a single command, and NeulinkAI will retrieve, analyze, and refine the information accordingly.

• Natural Language Queries – Users describe their requirements in plain language rather than applying multiple filters across different platforms.

• Multi-Variable Conditions – Instead of isolated data points, queries can factor in multiple conditions, such as market trends, liquidity shifts, or trading behaviors.

• Real-Time & Historical Insights – NeulinkAI retrieves both up-to-the-second market data and historical trends for comparison and forecasting.

Example Use Cases

• “Retrieve the top 10 AI tokens by 24H trading volume and compare their 7-day price growth.”

• “Track new wallets accumulating more than 50,000 ARB over the last week and check if they’re still holding.”

• “Compare the last three Bitcoin halvings and analyze how quickly BTC reached new ATHs post-halving.”

Beyond Simple Search

Unlike traditional search tools that require multiple steps and separate sources for real-time and historical data, NeulinkAI automates the entire data retrieval, filtering, and structuring process. Users can refine or expand their queries instantly, unlocking insights that were previously inaccessible without technical expertise or extensive manual effort.

By streamlining multi-condition data retrieval, NeulinkAI ensures that both newcomers and experienced users can navigate Web3 with clarity, precision, and efficiency.