Standard
- 5 analyses per monthPlanned
- Core saved strategy historyPlanned
- Standard research queuePlanned
Public beta
Great backtests are easy.
Trust is the hard part.
Maple imports your trading strategy, backtests it against real market data, and runs a full validation stack to answer the only question that matters: can this result actually be trusted?
Every strategy goes through the same pipeline
- Import
- Backtest
- Validation
- Trust Report
Performance and trustworthiness are different questions.
A strategy can post spectacular historical returns and still be built on luck, overfitting, or too little data. Maple scores the two separately — how well a strategy performed, and how much evidence supports that performance — so a beautiful equity curve never gets to speak for itself.
Performance
What the strategy did on historical data.
Evidence quality
How much of that result survives scrutiny.
See it work
Twenty seconds inside a real research session.
No script, no edited numbers — Maple running against real data.
Research you can keep, compare, and export.
An analysis isn't a one-off score — it's a record you build on.
Saved Research
Every analysis is saved in your library — results, settings, and the full Trust Report.
Version history
Refine a strategy over time and keep every version's results side by side.
Comparisons
Put two runs next to each other and see exactly what changed.
Export
Take the complete analysis with you as a portable research package.
Pricing
Simple pricing.
Honest analysis.
Maple is unfinished and in public beta. Strategy compatibility is still expanding.
Public Beta
Standard
$30/monthRegular price
$1 / month
Full Public Beta Access
The complete current Public Beta product at Maple’s lowest support price.
Current Public Beta access:
- Pine Script compatibility analysis
- Deterministic strategy parsing
- Automatic backtesting
- Monte Carlo simulation
- Walk-forward validation
- Out-of-sample testing
- Strategy grading
- Trust Report
- Improvement recommendations
- Saved Strategies workspace
- Compatibility Review submissions
- Community Discord access
- Current Public Beta analysis limits
Public Beta
Professional
$100/monthRegular price
$10 / month
Same Beta Access + Extra Support
The same current Public Beta product for users who voluntarily want to contribute more toward building Maple.
Choosing Professional during beta does not currently unlock additional product features. It is an optional higher support contribution.
Current Public Beta access:
- Pine Script compatibility analysis
- Deterministic strategy parsing
- Automatic backtesting
- Monte Carlo simulation
- Walk-forward validation
- Out-of-sample testing
- Strategy grading
- Trust Report
- Improvement recommendations
- Saved Strategies workspace
- Compatibility Review submissions
- Community Discord access
- Current Public Beta analysis limits
Expected after Public Beta
Planned full-release plan differences
These are directional plans, not current entitlements. Every item below is unavailable during the current beta unless Maple announces otherwise.
Professional
- Unlimited analysesPlanned
- Priority compatibility supportPlanned
- Early access to new Pine compatibilityPlanned
- Faster analysis queuePlanned
- Advanced research historyComing Soon
- Extended saved strategy historyPlanned
- Priority feature accessPlanned
- Upcoming Quant++ integrationNot yet available
- Future premium research toolsPlanned
No automatic price increase will occur without advance notice and consent. Cancel anytime. Unsupported compatibility submissions remain free and unlimited.
How It Works
From idea to evidence,
one honest pipeline.
Every strategy takes the same path. No shortcuts, no cherry-picking — the same tests, in the same order, every time.
Import
Paste Pine Script or describe the strategy in plain English.
Interpret
Maple parses it into a structured, testable specification.
Backtest
The strategy runs against real historical market data.
Validate
The full validation stack stress-tests the result.
Trust Report
Performance and evidence quality, scored separately.
Save
The complete analysis lands in your research library.
Compare
Line up versions and rival strategies side by side.
Export
Take the full report with you.
What "Validate" actually means
Six independent ways of asking the same question: does the evidence hold?
Out-of-sample
Tested on data the strategy never saw.
Walk-forward
Re-validated across rolling windows of time.
Monte Carlo
Thousands of resampled outcome paths.
Regime analysis
Behavior across different market conditions.
Robustness
Sensitivity to small parameter changes.
Drawdown
Depth, duration, and recovery of losses.
Examples
Excellent historical performance.
Not enough trustworthy evidence.
A real strategy imported into Maple: Legend BUY/SELL. On the surface, the backtest is outstanding. The Trust Report tells a more complete story.
What the backtest shows
- Return
- +57.07%
- Win rate
- 68.4%
- Profit factor
- 3.61
- Sharpe ratio
- 10.56
What the Trust Report found
- Performance score
- 87 / 100
- Evidence Quality
- 20 / 100
- Confidence
- Insufficient
- Grade
- Withheld
Every performance number above is real — Maple computed them. But performance only describes what happened on one slice of history. When the validation stack searched for independent evidence to support those numbers, it found too little to bear their weight.
So Maple scores the performance honestly, scores the evidence honestly, and withholds the grade. Not because the strategy is bad — because the available data can't yet prove it's good.
That's the difference between a backtest and research.
More of the analysis workflow
See how Maple presents uncertainty and risk.
The original Trust Report example above uses a verified Maple result. The visualizations below are clearly marked synthetic previews of additional research views.
Illustrative Example
Synthetic example dataMonte Carlo Simulation
A distribution-first view of how one strategy could behave across 500 simulated outcome paths.
Simulated equity growth
Simulated paths90% confidence regionMedian path
- Median Return
- +14.8%
- 5th Percentile
- −11.6%
- 95th Percentile
- +38.9%
- Probability of Loss
- 18.7%
- Expected Drawdown
- −9.4%
Example Visualization
Synthetic example dataDrawdown Analysis
Equity, loss depth, and time-to-recovery shown together so risk is not reduced to one headline number.
Equity and drawdown
Equity curveDrawdown depthRecovery point
- Maximum Drawdown
- −18.7%
- Recovery Time
- 74 days
- Recovery Factor
- 2.3×
- Longest Drawdown
- 112 days
- Worst Month
- −7.8%
These visualizations use synthetic values to demonstrate Maple’s research presentation. They are not user results, investment performance, or a promise of future returns.
Learn
The concepts behind
honest research.
Maple's public knowledge base — guides, methodology, and reference, in plain English.
About
Performance is easy to show. Trust is harder to prove.
Every trading tool can render an equity curve that goes up and to the right. Maple exists for the harder question underneath it — whether the evidence actually supports the result. That's a slower, humbler kind of research. We think it's the only kind worth doing.
Maple started from a simple frustration: most trading tools make strategies look impressive without helping you understand whether they're actually reliable.
It's being built to slow the process down, ask better questions, and make research feel understandable instead of intimidating.
Maple is built by Noah, out of a real interest in trading research, markets, and quantitative testing — and shaped by the discipline of the mountains: patience, humility, and preparation.
It's early. But the mission is clear: help people make better research decisions before risking capital.
Noah BergenFounder, CEO, CTO & CFO
Ryan DeethCo-Founder & Chief Marketing Officer
Recent updates
July 26, 2026Latest
Trust Report and Strategy Import Redesign
- The Trust Report has been redesigned to lead with a clear verdict. Instead of a dashboard of scores competing for attention, the report now opens with one answer — can this strategy be trusted, why, and what to do next — followed by a performance snapshot, supporting evidence, strengths and weaknesses, and recommended improvements. The full technical audit (methodology, diagnostics, raw evidence) is still there in full, one click away.
- Strategy Import now leads with a plain-English "Strategy Summary" — what a strategy actually does: its buy and sell conditions, exit rules, risk management, indicators, asset, and position size — before any parser or verification detail. The complete technical breakdown is preserved underneath, collapsed by default.
- Reordered the Strategy Import page so it reads the way you actually use it: paste a strategy, see the Trust Report and its summary, then save or export — instead of save/export controls appearing above the report they act on.
- Rebuilt the marketing site's mobile navigation as a proper slide-out menu, and simplified the Learn section into a single browsable index.
- Numerous smaller consistency fixes across the app: removed leftover "private beta" wording now that Maple is in public beta, cleaned up duplicate confirmation badges, and fixed a redundant technical-details toggle in the Compatibility Queue review flow.
July 25, 2026
Maple Public Beta Is Live
- Maple is now available in public beta.
- This release introduces Maple's complete strategy research workflow: import a Pine Script or plain-English strategy, select a market and timeframe, and run deterministic analysis across backtesting, Monte Carlo simulation, out-of-sample testing, walk-forward validation, robustness checks, and drawdown analysis.
- Every completed analysis produces an evidence-based Trust Report, plain-language findings, and actionable recommendations. Research can be saved in a persistent workspace with strategy versions, analysis history, run comparisons, and reproducible results.
- The public beta also includes authenticated accounts, protected market-data and AI services, subscription billing, usage controls, and server-enforced paid feature access.
- This is the beginning of Maple's public release. We'll continue improving strategy coverage, research clarity, performance, and the overall workflow based on real user feedback.
July 16, 2026
- Strategy Import now breaks down every imported strategy into a clear checklist — entries, exits, risk management, indicators, filters, position sizing, assets, and timeframe — so you can see exactly what Maple found and confirmed, what it had to assume, and what it didn't detect at all.
- Strategy Import now tells you what kind of strategy you imported — whether its signal logic looks like trend-following, mean reversion, or a breakout, and whether its holding-period cadence looks like scalping, swing trading, or a longer-term position — along with the specific reasons behind that read. When there isn't enough in the strategy to say confidently, Maple tells you that plainly instead of guessing.
July 15, 2026
- Maple has moved from a limited, request-only private alpha to a private beta with a single, permanent, self-serve access code — no more waiting for an invite.
- Strategy Import now understands older TradingView Pine Script (v3/v4), not just the newest v5 syntax — paste an older script and Maple converts it automatically before importing, no manual rewriting needed.
- Import warnings now point to the exact line in your script that needs attention, instead of a general notice.
- Strategy Import now recognizes a script's commission, slippage, and position-sizing settings and tells you plainly which of them carried over and which didn't, instead of leaving them out unmentioned.
- Strategy Import now catches broken syntax (like a missing quote or an unclosed parenthesis) precisely — a stray typo no longer silently swallows the rest of your script. You'll see exactly which line has the problem, and if it affects code further down, Maple tells you how much was skipped and how many rules were involved, instead of one generic warning.
July 14, 2026
- Your Dashboard, Backtests, Paper Trader, and Strategy Lab/Import now work in all 10 of Maple's supported languages — not just the app's menus and homepage.
- Prices, percentages, and trade counts now always read left-to-right, even inside Arabic's right-to-left layout, so financial figures never get visually reordered.
- Improved the language selector's default and hover border visibility on the homepage and in Settings, so it's clearly legible in every theme and state.
July 13, 2026
- Sped up Maple's homepage on mobile — the hero photo now loads a size matched to your device instead of one large desktop image for everyone.
- Improved the language selector's legibility and keyboard/screen-reader support across every theme and state.
July 10, 2026
- Prepared Maple AI Review infrastructure with usage limits, cost safeguards, and staged validation.
July 8, 2026
- Strategy Import is live — paste a plain-English strategy or TradingView Pine Script, and Maple shows what it understood, what still needs your input, and what it can't support, before you run anything.
- Unsupported or ambiguous parts of an imported strategy are disclosed as warnings, never silently dropped or guessed at.
- Imported strategies run through the same backtest and full-validation tools as the rest of Maple, and can export a cleaned-up plain-English or Pine Script version.
July 5, 2026
- Launched a public knowledge base at /learn — how Maple works, methodology, and more, no login required.
- Improved how search engines and AI tools see Maple's homepage.
July 4, 2026
- Added an in-app feedback button so you can report bugs or ideas from anywhere in the app.
- Opened a Discord community with an automatic alpha-code request flow.