Equinox Ai - Whitepaper
  • Overview
    • Introduction
    • Problem Statement
    • Solution (What is Equinox AI?)
  • Core Features
    • On-Chain Intelligence
    • Off-Chain Intelligence
    • Mixers & Bridge Tracking
    • Social Mapping (Telegram + X)
    • Equinox Protection (Privacy Layer)
  • Architecture & Technology
    • Technical Architecture
    • Behavioural Pattern Detection
    • Data Infrastructure & Indexing
  • Token + Model
    • $ENOX Utility
    • Tokenomics
    • Revenue Model
    • (E-Mask) Opt-Out System
  • Compliance & Vision
    • Roadmap & Vision
    • Security & Privacy Notes
    • Fair Use Disclaimer
  • Data Brokerage & Expansion
    • Whitelabelling & Platform Licensing
    • Data Intelligence Streams
    • Strategic Positioning & Market Outlook
  • Important Links
    • X
    • Whitepaper
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  1. Architecture & Technology

Technical Architecture

PreviousEquinox Protection (Privacy Layer)NextBehavioural Pattern Detection

Last updated 5 days ago

Equinox AI is structured as a high-performance, multi-layered infrastructure engineered to correlate blockchain behaviour with decentralised social activity in near real-time. Each layer of the system is designed with performance, modularity, and privacy-control in mind, allowing us to deliver complex behavioural data in a clean and queryable format.

System Overview

[Data Collection Layer] → [Processing Layer] → [Analysis Layer] → [Data Serving Layer] → [Interface Layer]

1. Data Collection Layer

This is the backbone of Equinox AI. The platform continuously ingests:

• On-chain Data: Multichain RPC and WebSocket-based transaction fetchers with native indexing for Ethereum, BSC, and L2s. • Off-chain Data: Scraping bots for Telegram groups, public X accounts, Discord servers, GitHub activity, and web2 endpoints. • Storage: Raw logs are time-stamped, hashed, and tagged by data type before being pushed to a distributed data lake.

2. Processing Layer

At this layer, raw inputs are transformed into usable records:

• Data Normalisation: Converts blockchain logs and social data into a unified schema. • Linkage Engine: Detects alias overlaps across usernames, wallets, and public messages. • Sequencer: Arranges token flows, mixer hops, bridge routes, and social events in chronological trails.

3. Analysis Layer

Here, the intelligence begins to form:

• Pattern Recognition: Machine learning models that score social-financial behaviour. • Entity Grouping: Clustering based on shared wallets, post timing, or trading behaviour. • Custom Alerts: Developer-tunable rules for behavioural thresholds, flagging, and risk scoring.

4. Data Serving Layer

All computed data is served through structured access:

• Caching Engine: Reduces latency for common wallet or group queries. • Graph DBs: Stores social–wallet–token links in a retrievable graph structure. • Rate-Limited API: Ensures equitable bandwidth distribution for dApp, partners, and backend tooling.

5. Interface Layer

The visible layer of Equinox:

• Equinox dApp: Web interface to explore analytics, scan identities, and monitor wallets. • Builder Portal: Advanced toolkit with custom API generation, report exports, and SDKs. • Partner Tools: Access modules for analysts, security auditors, and exchanges.

Smart Contract Stack

• ENOX Token: ERC-20, with built-in burn hooks for cloaking behaviour.
• Opt-Out Contract: burn-to-delist feature with Merkle root tracking for accountability.
• Billing Mechanism: optional fee model for third-party API calls and integrations.

Tech Stack Summary Table

Layer
Tech Used

Blockchain Access

Alchemy, Infura, QuickNode, custom RPC relays

Social Indexing

Python, Puppeteer, Selenium, NodeJS

Analysis Engine

Python (Pandas, NumPy, Scikit), Rust, Jupyter

Frontend

React, Tailwind, Next.js, WebSockets

Backend API

FastAPI, PostgreSQL, Redis, TimescaleDB

Infra

Docker, Kubernetes, NGINX, Cloudflare, S3

Equinox AI's architecture is purpose-built to evolve with the ecosystem. As new dApps, bridges, chains, or communication platforms emerge, our plug-and-play design ensures they can be integrated with minimal downtime and no overhaul. This foundation supports future upgrades such as ZK-layer enhancements, wallet fingerprinting, and advanced wallet–social trust scoring models.