Core Technologies

Documentation Index

Fetch the complete documentation index at: https://whitepaper.neurobro.ai/llms.txt

Use this file to discover all available pages before exploring further.

​

Overview

Neurobro’s intelligence layer is built on two foundations:

• Data: The highest quality financial data - real-time, multi-source, and proprietary - covering on-chain activity, market feeds, news, and social signals
• Agents: Autonomous AI components that process data, generate insights, and serve users across all platforms

This architecture enables a single intelligence to power every product in the ecosystem - from Neurodex to the mobile app to NeuroAPI - while maintaining consistency and quality.

​

Agents & Nevron

Behind Neurobro’s intelligence lies a network of specialized “Nevrons” - modular AI agents working in harmony. 200+ Nevrons work together to form a unified financial intelligence. Each Nevron handles specific tasks - from market analysis to sentiment tracking to on-chain research - forming the building blocks of our ecosystem. Nevrons communicate with each other, enabling complex multi-step analysis, decision-making, and research workflows. Some Nevrons also interface with external systems: executing trades, posting analysis, and interacting with users across platforms. To enable this architecture, we built our own agent framework called Nevron. The Nevron framework is open source and available on GitHub, with comprehensive technical documentation to help you get started.

​

Why Nevron?

It’s very important to understand that Nevron is not a general-purpose framework, but a framework specifically designed for building specialized AI agents. Here’s why to use it:

​

Shared Resources

Neurobro maintains a unified state across platforms through shared resources. Many different Nevrons work together on the same foundation of data and knowledge.

​

Agent Components

Neurobro appears as a single agent, but from a technical perspective, it is more complex. Neurobro includes multiple components that work together to provide both intelligence and functionality. Here’s an overview of the architecture: Since the main intelligence is focused on the main product-Neurodex-see there for more details.

​

Large Language Models

LLMs form the backbone of the AI, powering Nevron agents with advanced intelligence capabilities. Neurobro is model-agnostic by design. We route across a range of leading frontier and open-source LLMs, selecting the right model for each task - and continuously evaluating and swapping models as the landscape evolves. Different categories of work call for different strengths:

​

Platform-Specific Examples

While Neurobro, as an AI agent that encompasses all the Nevrons, remains a single agent, its presence on different platforms significantly varies. Here are some examples of how Neurobro works across different platforms:

​

Data

GIGO = Garbage in, garbage out

AI agents are only as good as the data they process. This is why we invest heavily in building a proprietary financial data infrastructure - the highest quality, most comprehensive data layer we can build. This is the second foundation of Neurobro’s intelligence.

​

Agent Memory

Agent Memory is similar to human memory, but for AI Agents. It consists of opinionated data points about the ecosystem the agent operates in. We currently use a blend of vector stores and graph databases to store this representation of memory. A crucial part of the vectors are embeddings. All embeddings are generated using state-of-the-art embedding models, ensuring:

​

On-Chain Data

We track 3,000+ whales on Base chain and analyze their activity in near real-time. Our proprietary ML labeling system transforms raw, noisy on-chain data into a clean, structured intelligence layer. This data feeds directly into specialized Nevrons for analysis and is also exposed to users through the Smart Money Dashboard on Neurodex.

​

News, Social & Sentiment

We aggregate financial news, social media signals, and market commentary from across the web. RSS feeds, X API integrations, and other sources provide a continuous stream of market-relevant information. Since raw social and news data is extremely noisy, specialized Nevrons filter, aggregate, and deduplicate information - maintaining a clean, up-to-date knowledge base.

​

Market Data

Technical market data (pricing, volume, liquidity, order books) is sourced from a combination of proprietary and leading third-party market data APIs.

​

Proprietary Data Layer

The majority of Neurobro’s value comes from proprietary data processing and analysis. We do not disclose full details of our data sources for competitive reasons.

​

Conclusion

Neurobro’s intelligence is built on two pillars: specialized AI agents and a proprietary financial data infrastructure. The combination of a comprehensive data layer with asymmetric access to market information, plus an AI architecture designed to exceed the limitations of standalone LLMs, is what enables Neurobro to deliver institutional-grade financial intelligence to everyone.