# StratCraft Product Detail

> StratCraft is an AI-assisted platform for building local trading systems.

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

The product helps users move from 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 a local quant workflow 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
- inspect and iterate on generated code
- run backtests locally
- 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
- 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
- Python strategy authoring
- 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/)