Maple is early-stage software, currently in a private alpha with a small group of invited testers. This page describes the direction the product is headed in broad terms, rather than a fixed, dated feature list — plans change as the team learns from real testing.
Current focus
The immediate priority is strengthening the core research loop — backtesting, validation, and the Strategy Lab — based on direct feedback from alpha testers, and making sure the statistical validators (see Methodology) are as rigorous and clearly explained as possible.
Directions being explored
- Expanding the set of statistical validators and making their explanations more detailed for users who want to go deeper.
- A research journal for keeping a running, organized record of what's been tested and learned over time.
- Broader asset and market coverage for backtesting and paper trading.
- Continued refinement of the AI-assisted research tools, always kept clearly separate from the deterministic engine that computes actual results.
What won't change
Regardless of which features ship, Maple's underlying commitment stays fixed: research and validation over promotion, transparency about how results are computed, and no framing of Maple's outputs as financial advice or guaranteed performance.