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Open-source · AI-native · Built for Interactive Brokers

Build your edge from your own data.

Tradelogue connects your trades, journal, rules, and market context to uncover patterns, challenge bad habits, and show you what to work on next.

GitHub release coming soonExplore the product
Performance + session summary
Tradelogue dashboard showing demo performance, market brief, and recent sessions
Analytics + recent sessions
Demo data

AI coach

Find the patterns humans miss.

Tradelogue reviews your full journal—not one isolated trade—to connect recurring mistakes, strengths, blind spots, and the conditions behind your best decisions.

  • Three focus areas grounded in your history
  • Strengths and recurring mistakes with evidence
  • Suggested experiments and follow-up chat
Focus areas + evidence
Tradelogue AI coach showing three focus areas and evidence-backed pattern analysis using demo data
Blind spots + next experiments
Demo data

Rules and discipline

See exactly what broken rules cost you.

Define the process you want to follow, then review violations by session, rule, count, and affected P&L. The relationship between discipline and results becomes visible.

  • Zero-to-two, three-to-five, and six-plus violation cohorts
  • Violation counts and affected P&L by rule
  • AI-suggested rules remain yours to accept or reject
Violation cohorts
Tradelogue discipline analysis comparing violation cohorts and affected P&L using demo data
Rule cost breakdown
Demo data

Setups and playbooks

Build around the setups that hold up.

Name the playbooks you trade, tag each execution, and compare performance by setup. Tradelogue can suggest a missing setup without silently changing your journal.

  • User-defined setup library
  • Performance by setup, ticker, weekday, and entry hour
  • Reviewable AI setup suggestions
Opening range reclaim
Tradelogue setup catalogue with performance summaries using demo data
Trend continuation
Demo data

Voice journal

Talk through the trade while it is still fresh.

Record the thesis, entry, exit, and execution in your own words. AI turns the transcript into structured notes, proposes a setup, and grades the decision with a reason you can review.

  • Voice or text capture
  • AI-refined thesis and execution notes
  • Trade grade, rationale, chart, duration, entry, exit, and P&L

Roadmap: automatic chart retrieval and entry/exit overlays.

Chart
Tradelogue trade detail with chart, metrics, structured notes, setup, and grade using demo data
Trade metrics
Record + setup + thesis
Grade + rationale + execution
Demo data

Market context

Start the session with the context in one place.

Review index snapshots, economic events, earnings, top stories, and the day’s rule focus before opening the journal. Market briefs use the providers you configure.

  • Index and volatility snapshots
  • Economic calendar and earnings in focus
  • Top stories, stocks in play, and market posture
Market overview + top stories
Tradelogue market brief with index snapshots, economic calendar, earnings, and top stories using demo data
Calendar + earnings
Demo data

The evidence layer

Measure the process, not just the result.

Coaching starts with a dependable record. Tradelogue keeps the analytics and review tools close without making the dashboard the whole story.

Core analytics

Win rate, profit factor, expectancy, average win/loss, and streaks.

Performance views

Performance by ticker, weekday, entry hour, and setup.

Review cadence

Calendar and per-session review.

Product themes

Light and dark product themes.

IBKR imports

Automatic IBKR Flex sync and manual Flex XML import.

A closed improvement loop

Every review should change the next decision.

Tradelogue connects executions to context, context to patterns, and patterns to a specific experiment.

  1. 01

    Sync

    Import executions from IBKR automatically or from Flex XML.

  2. 02

    Journal

    Add context by voice or text and attach the chart.

  3. 03

    Discover

    Let rules and AI surface patterns, strengths, and blind spots.

  4. 04

    Improve

    Choose focus areas, test experiments, and measure the result.

Open source, in practical terms

Your journal should not be a black box.

Tradelogue is available for local or self-hosted operation. Interactive Brokers is the only supported broker today.

GitHub release coming soon

Local by default

Run Tradelogue on your machine or self-host it in your own environment.

Bring your providers

Use your own supported AI-provider and market-data credentials.

Inspect the logic

Rules, analytics, and coaching flows remain open to review and contribution.

Control the data

Journal data stays under the operator’s control in their own deployment.

Contributions and issue reports are welcome once the public repository is available.

Explicitly future work

Roadmap, not release notes.

Future

Chart retrieval and overlays

Automatic chart retrieval and entry/exit overlays.

Future

Additional brokers

Additional broker import adapters.

Future

First-run onboarding

Easier first-run setup and demo-data onboarding.

Future

Self-hosting packaging

Packaging improvements for self-hosters.

Before you run it

Questions, answered plainly.

What does Tradelogue do?

Tradelogue is an open-source, AI-native trading journal for coaching, pattern discovery, rules, analytics, and disciplined review.

Does Tradelogue place trades or provide signals?

No. Tradelogue does neither; it is journaling and analytics software, not financial advice.

Which broker is supported?

Interactive Brokers is the only supported broker today.

Can I run it locally or self-host it?

Yes. Tradelogue runs locally or can be self-hosted.

What credentials do I need?

Market brief generation depends on configured market-data providers and an AI provider. Bring your own supported credentials.

What happens to my data?

Data remains under the operator’s control in their own deployment.

Is there a hosted version?

No hosted SaaS is available at launch.