Finance and accounting decision
Aimytrade.io
A capable technical user can build a useful self-hosted replacement using existing open-source projects (notably the cited LLM-driven stock analysis repos) and public market/EDGAR feeds; the SaaS mainly packages data aggregation, the 33-factor scoring and UX/ops polish.
Visit website↗$9/mo
$108/yr
Read off the official pricing page.
$100one-off56 h to build
$50/mo6 h/mo upkeep
On cash alone, building overtakes the subscription at 7 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 Aimytrade.io alternatives, with the arithmetic →
What a replacement has to do
- 1) Fetch and normalize market and historical price data (Yahoo/IEX/Finviz). 2) Ingest and parse SEC filings (Form 4, 13F) and news/social feeds (Reddit/News RSS). 3) Compute technical indicators and the 33-factor scoring model. 4) Run an LLM/templating step to synthesize factor breakdown and natural-language analysis. 5) Serve a single-page UI + backend API to request an analysis and display factor breakdowns.
What it still won’t have
- Polish and UX refinements (mobile, in-app notifications, watchlist UX)
- Proprietary historical datasets and any curated signal tweaks or paid data feeds
- Priority support, early-access features, and product roadmap improvements
- Operational reliability and data-aggregation SLAs provided by the SaaS
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 7 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 self-hosted minimal AimyTrade-like analytics app using Python (FastAPI), Postgres, Celery/RQ for background jobs, React for a single-page UI, and Redis for caching. Core features in scope: (1) fetch historical & intraday quotes from Yahoo Finance / IEX and cache; (2) fetch and parse SEC EDGAR Form 4 and 13F filings and basic news/Reddit feeds; (3) compute common technical indicators (RSI, MACD, moving averages, Bollinger Bands) and implement a configurable 20–33 factor scoring pipeline that emits per-factor raw values and weights; (4) integrate an LLM (OpenAI or compatible) to generate a short rationale and checklist from the factor outputs; (5) provide an API endpoint to request an analysis by ticker and a React page showing conviction score, factor table, entry/exit/stop levels, and raw evidence links. Out of scope: trade execution, paid proprietary data vendors, advanced options-flow ingestion, enterprise-grade multi-tenant billing. Require error handling for external API failures, retries, idempotent background jobs, unit tests for scoring logic, and end-to-end tests for the analysis flow.
How we checked
How the score was reached
- Partly verdict base52
- An open-source build was found+5
- 5 cited sources+3
- Price verified on pricing page+3
- 3/3 assessment runs agreed+4
- Evidence score67
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 · 5
Every page the run actually retrieved.
- official productAimyTrade — official product
- official pricingPricing — AimyTrade
- official docsHow it works — AimyTrade
- open sourceOpenBB-finance/OpenBB
- open sourceZhuLinsen/daily_stock_analysis
Integrity checks
What held up, and what did not.
