VTX Macro

Overview

VTX Macro is a live AI trading platform for cryptocurrency markets that combines autonomous trade execution, real-time market analysis, and strategy management in a single system. Built around the Hyperliquid exchange, it allows users to run cloud-hosted AI traders 24/7, monitor decisions in real time, and iterate on strategies through analytics and configuration snapshots. The platform processes thousands of AI prompts per day and has executed thousands of trades across hundreds of thousands of dollars in trading volume.

The Problem

Most traders and quantitative builders must stitch together market data feeds, exchange APIs, model providers, risk controls, and monitoring tools themselves. This creates operational fragility, poor visibility into AI behavior, and significant engineering overhead just to run and evaluate automated trading systems.

The Solution

VTX Macro consolidates market data ingestion, AI analysis, and exchange execution into a single integrated platform. Users can configure models, run autonomous trading bots in the cloud, inspect every decision, and refine strategies using built-in analytics, guardrails, and reusable configuration snapshots.

Core Capabilities

• 24/7 autonomous AI trading on Hyperliquid with live execution and server-side dry-run AI Assistant mode
• Multi-model orchestration with BYOK support across direct providers and aggregators
• Configurable strategy engine with indicators, timeframes, and reusable settings snapshots
• Integrated risk controls including stop loss, take profit, killswitches, and performance guardrails
• Full decision transparency through searchable trade history and AI reasoning logs
• Insights workspace with retrieval-augmented analysis over trading data and live market context
• Analytics, public profiles, leaderboards, and snapshot sharing for collaboration and strategy discovery

Technical Overview

The system is built as a monorepo with a microservices-style architecture using Next.js and TypeScript for the frontend and FastAPI with Python services for the backend. Background trading loops and analysis workers run asynchronously while PostgreSQL stores persistent trading data and Redis manages runtime coordination and caching. WebSocket connectivity provides real-time market data and execution workflows, enabling low-latency AI-driven trading decisions.