Sandbox script platforms cap your strategy at 500 lines of interpreted code inside a locked-down environment. The allowed imports are basic math libraries. Network, threading, database access: all prohibited. The result is a structural ceiling that no amount of UI polish can fix.
The difference is not features. It is architecture.
| Dimension | Sandbox Platforms | StratCraft |
|---|---|---|
| Strategy language | ~500-line pandas / Pine Script | C++23, Python, AI-generated code |
| Execution performance | Interpreted, single-threaded | Compiled C++23, SIMD/AVX-512 vectorized |
| Strategy composition | Single-indicator logic (one signal per strategy) | Combinator pipeline: Factors ML Signals Hypotheses Indicators → Linear / ML combination |
| Data access | Sandbox-restricted (no network, no file IO) | Multi-source, multi-frequency, alternative data |
| AI / ML integration | Chat assistant (no code generation) | Supported BYOK or local-model authoring plus separately admitted ML research |
| Plugin architecture | No plugins (closed sandbox) | Process-isolated plugins via gRPC, hot reload |
| Scalability | 1 strategy at a time | Governed multi-strategy research operations |
| Deployment | Docker + manual env config | Local research workflow; deployment is not a current product claim |
| Factor research | Not possible in sandbox | Alpha factors, expression trees, IC/ICIR — composable inputs to Combinator |
| Market edge potential | Public signals only (no edge) | Inspectable combination with evidence; no market-edge claim |
Why architecture affects which research operations are possible
Every one of these is a public signal. Thousands of free TradingView indicators do the same thing. There is no market edge here.
None of these fit inside a 500-line sandbox. They require compiled performance, unrestricted data access, and extensible architecture.
Sandboxes have their place for specific use cases.
Serious research requires serious infrastructure.
The ceiling should be your strategy idea, not your tool.