Jango

Jango automates the full quant workflow: a team states a hypothesis — a breakout pattern on a crypto pair, a sector signal buried in federal procurement data — and agents handle backtesting, strategy refinement, and live execution inside managed books. The loop is closed by design. You are not moving results between tools; the agent runs from test to trade. Real-position trading with funded accounts is the target environment, not paper trading or simulation.

The differentiating claim is the agentic layer itself. Rather than a scripted pipeline where each step waits for a human handoff, the agents plan and react — branching based on what the prior step returned, recycling winning positions into cash-flow strategies without a manual trigger. For teams managing multiple concurrent strategies, that autonomy is the point.

Where Jango fits: quantitative traders who have already validated a strategy approach and want execution automated at the position level. Where it breaks: teams that need fine-grained visibility into agent decision logic — why a position was sized a certain way, what signal triggered an entry — will find the vendor page offers no detail on audit controls or explainability tooling. Teams in regulated environments, or those whose risk process requires human sign-off before any live entry, should treat that gap as a blocking issue until confirmed otherwise with the vendor.