Discretionary traders live on pattern recognition — but manually proving a pattern across thousands of sessions is impossible. Chartnaut's autonomous research agents scan 13+ years of market data, find every occurrence, and return the statistical reality.
Plain English in. Evidence out.
“Do opening gaps usually fill?” “What happens after failed auctions at prior highs?” Every discretionary trader asks these questions. The problem is proving them — manually scanning charts takes hours, sometimes days, and you'll always miss occurrences.
Describe the pattern in plain English. Our autonomous agent scans thousands of market days, finds every matching occurrence, classifies the outcomes, and returns the evidence — no cherry-picking, no bias.
“Find all instances where price broke above the previous day's high, then retraced back inside the range within 30 minutes”
Your playbooks, backtesting sessions, and research studies contain answers you've never had time to find. Chat surfaces them — in plain English, with full trading context.
“Which tag combinations have the highest win rate?” “What's my average R on gap days vs. non-gap days?” Ask anything — the AI understands R-multiples, timeframes, TPO, and market structure.
Which tag combinations have the highest win rate in my ES playbook?
Based on your ES playbook (312 trades), here are your top performing combinations:
Run hypotheticals on your playbook data. “If I let my winners run longer, do I make more profits?” “What if I filtered out low-volume days?” Ask “what if” questions and see how rule changes would have affected your historical performance.
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If I let my winners run longer, do I make more profits?
Analyzing hypothetical rule changes against your historical data...
AI finds every occurrence — good and bad. No cherry-picking.
Days of chart review compressed into minutes.
Ask follow-ups. Add filters. Refine your edge.
Approve the research plan, walk away. It runs in the background.
Chat and Study Mode are research tools — not trading advisors. AI-generated insights should always be verified. The agent finds patterns in historical data, but you make the trading decisions.
Describe the pattern you've been curious about. Ask the question you've always wanted answered. Your data is ready to talk.