AI Trading bot orderbook analysis in Python using Gemini 3, cryptocurrency bitcoin and binance. In this video, I build a real-time Binance Futures orderbook scanner that detects hidden liquidity, order flow imbalance, and chart patterns using an AI-assisted workflow.

This project streams live Binance USDM-Futures data into a Python data pipeline, where multiple analysis layers run in parallel — L2 orderbook / order flow analysis, Elliott Wave structure detection, and chart pattern recognition inside wave context. Instead of relying on candles alone, the system focuses on identifying invisible liquidity walls, traps, and imbalance as they form in real time.

In the final stage, all signals are combined into a single synthesis layer that calculates entry price, stop loss, and exit targets based on market structure and order flow context. This is Part 1 of the build, focused on the scanner and data pipeline. In the next part, I’ll add replay tools, alerts, and an AI copilot that explains what the system is seeing live.

What’s inside this build:
AI-assisted development using Gemini 3
Python real-time data ingestion & preprocessing
Binance Futures orderbook (L2) & order flow analysis
Elliott Wave structure scanning
Chart pattern detection within wave context
Signal synthesis → entry, stop loss, targets