Using Jev as a trading decision layer

A Jev trading setup does not predict prices — it turns signals you already compute into a typed, calibrated buy / sell / hold decision in milliseconds. Developers wire it into fast loops, including one decision per block on-chain, because Jev answers in roughly 70–500ms with a confidence score attached.

The Jev trading pattern is simple: you compute your own indicators — trend, momentum, relative strength, event risk — and pass them as structured state to Jev's gate primitive. Jev returns a typed decision plus a probability, so there is no free text to parse and no invalid action to guard against. The model never sees a chart; it evaluates the signals you defined against the rule you encode.

How the gate primitive makes the call

A gate is a yes/no under conditions. A community BUY gate looks like: trend > .75 AND momentum > .70 AND relative strength > .65 AND event risk < .40 AND overextended < .80. Jev evaluates all of those in one parallel pass and returns the decision with calibrated confidence, which you can threshold — act on high-confidence signals, hold on the low-confidence tail.

• Inputs: your own structured signals (trend, momentum, RSI, event risk, …)
• Primitive: gate for buy/sell/hold, or choice to pick among strategies
• Latency: ~70–500ms per decision — fast enough for one call per block
• Output: a typed action plus a confidence score, nothing to parse

What people have built

Open POCs show the Jev trading pattern end to end: per-block decision bots on-chain, HFT-style signal gates, and paper-only signal labs that log every call. A typical live session reports p50 around 386ms and p95 near 490ms with zero dropped decisions over hundreds of calls — the appeal is consistency and speed, not a market edge. You can reproduce the loop against POST https://jevtypesafeai.com/api/v1/decide with a jv_live_ key.

Not investment advice

This is educational: a Jev trading decision reflects the rule and signals you gave it, nothing more. Speed and calibration do not imply profit, and confidence measures how concentrated the distribution is, not whether the trade will work. Do not point this at real money without your own risk controls, backtesting, and understanding that markets can and do break any fixed rule.

See also: Jev use cases · How to use the API · Playground

Related: Jev AI agent · Jev classifier · System One model