What you can build with it

Purpose and audience

This self-hosted trading stack covers Python strategies, backtests, paper trading, live execution and monitoring.

Evidence 1 ↗

How Jev fits

Jev evaluates order, strategy, exposure, position and budget context, returning typed choices with probabilities for the entry filter.

Evidence 1 ↗

Using the project

Enable AI Decision Filter for a regular live strategy or Quick Trade, then configure Jev in System Settings → AI / LLM.

Evidence 1 ↗ · Evidence 2 ↗

Scope and limits

Exits bypass AI; grid, DCA and martingale are excluded. With no available AI provider, entries fail open. Live mode can submit real orders.

Evidence 1 ↗ · Evidence 2 ↗

Repository description

Open-source AI Trading OS, agent trading, and vibe trading, with Jev System One integration. Research, build Python strategies, backtest, and paper/live trade across crypto, stocks, and forex. Launch your own multi-tenant trading SaaS with built-in user management, billing, payments, and settlement.

Project facts

Relationship to Jev
Integration
Evidence
Documented
Language
Python
License
Apache-2.0
Origin
Original repository
Repository status
Not archived
Created
2025-12-28
Last code update
2026-09-26
GitHub stars
12,273
Evidence checked
Sep 30, 2026
Metadata checked
Sep 28, 2026
Check status
Up to date

Stars measure the whole repository, including work unrelated to Jev.

Evidence and scope

Documented records the linked documentation or source. JevHunt has not independently run or benchmarked this project.

Evidence commit: 709521ffd6df8460dc7bfaba0451258b0f1743da

Discovered through: typesafe-field-guide, github-search.

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