Analytics and monitoring decision
ChartsGPT
A single developer can reproduce the core screenshot→analysis workflow and a web-based assistant in about a week, but the full mobile product experience (native app, lock‑screen signals, App Store subscription polish and academy content) and any proprietary backend optimizations are not reproduced cheaply.
View on the App Store↗$12.99/mo
$156/yr
Read off the official pricing page.
$100one-off35 h to build
$120/mo3 h/mo upkeep
On cash alone, building overtakes the subscription at 10 seats.
Open-source builds that already do this
Every project below is open source and already does this job today. Fork one, self-host it, or take the parts you need - the build prompt further down assumes an empty file, and this is the shortcut past that. Licences differ; check the one on each card before you ship. All ChartsGPT alternatives, with the arithmetic →
What a replacement has to do
- Upload or photograph a chart → detect symbol/timeframe → extract structure/key levels → run rule-based technical-analysis engine → generate human-readable trade setup and score
What it still won’t have
- Native iOS app UX and App Store distribution (lock‑screen live signals and push notifications)
- Polished, production mobile UI/animations and built-in Academy content
- App Store subscription handling and built-in referrals/ratings
- Any proprietary backend optimizations or internal models not documented on the App Store page
What remains hard
- Product polish and ongoing maintenance
First-year cost
Keep paying
Paying is—cheaper in year one.
On cash alone, building overtakes the subscription at 10 seats.
Money you would actually spend
Time you would spend
—
What you would spend
What we assumed
The verdict above measures whether you could build it. This one is only about money.
Runnable build prompt
Build a small web service (React frontend, Flask or FastAPI backend, Postgres) that accepts a chart photo upload, identifies the market symbol and timeframe (use an OCR/vision model or OpenAI Vision), runs a rule-based technical analysis engine (trend, support/resistance, simple pattern detection) to produce entry/stop/target and a quality score, and uses an LLM (OpenAI-compatible) to render human-readable explanation and an interactive Q&A assistant. Core features in scope: image upload, symbol/timeframe detection, TA rules engine, LLM explanation pipeline, basic watchlist with live quotes via a market-data API, user account & saved analyses. Out of scope: native iOS app, App Store subscription integration, advanced Academy lessons, push notifications. Include error handling, input validation, unit tests for analysis logic, and deployment scripts (Docker + small cloud instance).
How we checked
How the score was reached
- Partly verdict base52
- An open-source build was found+5
- 2 cited sources+1
- Price verified on pricing page+3
- Evidence score61
The base comes from the verdict. Everything under it is a check that either happened or did not, and each one is a fact frozen in this record rather than a judgement made at render time - so the same evidence always produces the same number.
How scoring works →Cited sources · 2
Every page the run actually retrieved.
- official productChartsGPT: AI Chart Analysis - App Store
- open sourcetradesdontlie/tradingview-mcp
Integrity checks
What held up, and what did not.
