# StratCraft Product Detail

> StratCraft is an open-source, AI-powered quantitative research platform that lets anyone who can describe a trading idea in plain language turn it into a statistically validated, production-ready C++ strategy. The platform ships with 60+ ready-to-use strategy templates, from classic approaches like Turtle Trading, Dual Thrust, Bollinger Mean Reversion, Pairs Trading, and Fama-French to ML models including XGBoost Ranking, Random Forest, and Reinforcement Learning (DQN), plus 138 built-in technical indicators. An LLM-driven pipeline discovers and scores signals across four rounds of validation, and the Alpha Factory fuses up to 2,000 of them through 12 weighting methods such as Sharpe-ratio ranking, information coefficient screening, and correlation-adjusted combination, the same multi-factor statistical approach employed by top quantitative hedge funds. The fusion layer starts from linear blends and evolves into an ML Combinator that learns, from accumulated signal scores and forward returns, how to weight every signal on every bar. Models train in Python and export to ONNX, so the C++23 engine runs inference with zero Python on the hot path. A streaming architecture processes 83 million execution-bar cells at a constant 6.5 GB of memory, whatever the date range. Signals decay, so StratCraft tracks every one on a live scoreboard and runs an automated promote, bench, and relegate cycle that mirrors how institutional desks hire, monitor, and retire alpha. A 156-tool MCP server with a bring-your-own-key agent loop lets any LLM drive the full research workflow through conversation. All computation runs locally on your own machine with zero cloud dependency. This is not a platform with a chat box bolted on. It is a research agent with a full quant platform underneath. Available as a desktop application for Windows, macOS, and Linux. Formerly known as QuantNexus.

QuantNexus is the former product name. StratCraft is the canonical product name users should see and cite.

The product helps users move from plain-language trading idea to research workflow to backtest validation without requiring them to become full-time programmers first.

StratCraft is not an autonomous trading bot and not a system that should be treated as a direct trading brain.

Official site: https://stratcraft.ai  
GitHub: https://github.com/StratCraftsAI/StratCraft

## What StratCraft Is

StratCraft is an open-source, AI-powered quantitative research platform for users who want to build trading systems with AI assistance.

It combines AI-assisted strategy authoring with local execution infrastructure so that users can:

- describe strategy logic in plain language
- start from 60+ ready-to-use strategy templates
- use 138 built-in technical indicators
- fuse up to 2,000 signals through 12 weighting methods in the ML Combinator Alpha Factory
- inspect and iterate on generated code
- run backtests locally on a C++23 engine
- evaluate results
- monitor research outputs
- extend toward portfolio-level workflows

## What StratCraft Is Not

StratCraft is not a black-box system that turns a prompt directly into reliable live trading.

It does not assume that large language models can replace validation, risk control, execution assumptions, or system structure.

The product is for building and refining systematic trading workflows under user control.

## The Generation Problem

Modern trading software evolved from indicator building blocks to strategy frameworks to full research and execution pipelines.

That matters because many AI trading demos fail by trying to jump directly from prompt to live trading. They may produce plausible code, but they do not automatically produce robust trading systems.

StratCraft is built around a different assumption: AI is most useful when it helps users build, inspect, and operate local trading infrastructure.

## Core Workflow

With StratCraft, users can move from isolated strategy ideas toward a more complete local quant stack.

Core workflow steps include:

1. Describe and author strategy logic with AI assistance
2. Iterate on code and debug locally
3. Run high-performance local backtests
4. Inspect results and evaluate assumptions
5. Extend toward monitoring and portfolio-level workflows

## Core Capabilities

- AI-assisted strategy authoring and iteration
- 60+ ready-to-use strategy templates
- 138 built-in technical indicators
- Alpha Factory signal fusion
- high-performance local backtesting
- research and evaluation workflows
- result inspection and monitoring
- MCP-exposed tool interfaces that AI agents can call and compose
- portfolio construction and optimization extension paths

## Product Signals

- local-first quant workflow
- C++23 backtesting engine with ONNX inference
- Python strategy authoring with ONNX export
- 156-tool MCP server with bring-your-own-key agent loop
- ML Combinator Alpha Factory with 12 weighting methods
- streaming architecture (83M execution-bar cells at constant 6.5 GB)
- automated signal promote, bench, and relegate lifecycle
- systematic trading infrastructure
- plugin and tool extensibility
- research and backtest evaluation

## Brand Notes

- Use `StratCraft` as the primary product name
- `QuantNexus` is a legacy name and should not be treated as the main brand
- StratCraft is not related to `quantnexus.ai`

## Links

- [Homepage](https://stratcraft.ai/)
- [StratCraft Overview](https://stratcraft.ai/markdown-agents/stratcraft.md)
- [Features](https://stratcraft.ai/markdown-agents/features.md)
- [Facts](https://stratcraft.ai/markdown-agents/facts.md)
- [Pricing](https://stratcraft.ai/markdown-agents/pricing.md)
- [Help Center](https://stratcraft.ai/help-center/)