You will get Altora Recon Lite – AI Market Analyzer (TrapScore™ + Whale Detection)
Project details
Altora Recon Lite is a next-generation AI market simulation tool for researchers and traders who want to explore advanced phase detection and safe, pseudo-AI market logic. Unlike typical scripts, it blends simulation, algorithmic scoring, and alerting to surface market “traps” and whale imbalances in real time.
The modular CLI Recon Series (Lite → Live → AI Quant) evolves in clear steps: start with simulated TrapScore™, upgrade to real Bybit API data, then layer GPT-assisted signal processing. It stands out by revealing exactly how an AI-quant stack is built from zero, with transparent, reproducible outputs instead of opaque dashboards.
I specialize in rapid prototyping and structural AI system design, delivering clean, well-documented code that’s easy to extend. From simulation to live automation, each module is written, tested, and optimized for clarity, performance, and future scalability. Clients receive a working prototype, technical docs, and optional upgrades to Phase 2 or 3.
For quants, data engineers, and investors, Recon provides an explainable, visual, and expandable foundation—lightweight, elegant, and production-ready.
The modular CLI Recon Series (Lite → Live → AI Quant) evolves in clear steps: start with simulated TrapScore™, upgrade to real Bybit API data, then layer GPT-assisted signal processing. It stands out by revealing exactly how an AI-quant stack is built from zero, with transparent, reproducible outputs instead of opaque dashboards.
I specialize in rapid prototyping and structural AI system design, delivering clean, well-documented code that’s easy to extend. From simulation to live automation, each module is written, tested, and optimized for clarity, performance, and future scalability. Clients receive a working prototype, technical docs, and optional upgrades to Phase 2 or 3.
For quants, data engineers, and investors, Recon provides an explainable, visual, and expandable foundation—lightweight, elegant, and production-ready.
Machine Learning Tools
ChatGPT, GPT-3, NumPy, pandas, Python, PyTorch, scikit-learn, TensorFlowWhat's included
| Service Tiers |
Starter
$1,500
|
Standard
$3,000
|
Advanced
$5,000
|
|---|---|---|---|
| Delivery Time | 2 days | 4 days | 6 days |
Number of Revisions | 1 | 2 | 3 |
Model Validation/Testing | - | ||
Model Documentation | - | ||
Data Source Connectivity | - | ||
Source Code |
Optional add-ons
You can add these on the next page.
Additional Model Variation
(+ 1 Day)
+$150
Additional Scenario
(+ 1 Day)
+$100
Additional Graph/Chart
+$75
Model Documentation
(+ 1 Day)
+$120
Data Source Connectivity
(+ 2 Days)
+$200Frequently asked questions
About Shinya
AI & Algorithmic Trading Bot Developer
Clisson, France - 4:18 pm local time
I am an AI & Algorithmic Trading Bot Developer specializing in automated crypto trading systems using Node.js, Python, and OpenAI-powered decision logic. I build high-performance trading terminals that integrate CVD, OI, Order Book zones, funding rates, and whale flow analytics to generate high-confidence LONG/SHORT entries.
I design complete systems end-to-end, including API integration (Bybit/Binance), execution engines, risk monitoring, adaptive strategy logic (sideways/trending detection), and real-time UI dashboards.
If you are looking to build or optimize an AI-driven trading bot, enhance automation precision, or design a scalable strategy architecture — I can help deliver results.
Open for project discussion.
Steps for completing your project
After purchasing the project, send requirements so Shinya can start the project.
Delivery time starts when Shinya receives requirements from you.
Shinya works on your project following the steps below.
Revisions may occur after the delivery date.
Environment Setup and Webhook Configuration (Altora Recon Init)
I’ll configure your Discord webhook or test endpoint, validate connection stability, and prepare the environment for execution. This step ensures smooth TrapScore™ simulation and secure alert delivery before full model deployment.