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Developer Demo Applies TypeSafe AI's Jev to Real-Time Trading Decisions on Hyperliquid

September 17, 2026 at 23:16 EDT

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Foundation Models
Finance

A developer demo has paired TypeSafe AI's new Jev decision model with an autoregressive model trained on 12 billion data points to automate technical analysis on Hyperliquid, the on-chain trading venue. The system is described as making real-time decisions from time-series data, market indicators and live news feeds as conditions change.

September 2026 · TypeSafe AI

Jev Moves Into Real-Time Trading Tests

A developer demo applies Jev to technical-analysis decisions on Hyperliquid, combining time-series signals, indicators and live news context.

12B

data points in the paired autoregressive model

0.114s

sample Jev workflow completion time

$42

per billion input tokens

Workflow latency comparison

0.114s

Jev

8.566s

LLM comparison

The comparison highlights why low-latency decision models are being tested in live market workflows.

Potential fit

Fast bounded choices, confidence thresholds and structured outputs suit routing, guardrails and signal checks.

Critical limit

A valid structured output can still be the wrong market decision, especially when capital moves automatically.

Decision loop under test

Market state→Typed questions→Confidence score→Act or escalate

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