The Jev launch post
Diogo Almeida introduces Jev, TypeSafe’s structured decision model. Watch the launch film and explore the original thread for the model’s approach, examples and author-reported performance.
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Recent activityA FIELD GUIDE TO JEV / VOL. 01
The best of Jev. Real projects, practical guides and ideas from across the internet.
Diogo Almeida introduces Jev, TypeSafe’s structured decision model. Watch the launch film and explore the original thread for the model’s approach, examples and author-reported performance.
TypeSafe’s official launch announcement introduces the lab and points builders to Jev. It includes Diogo Almeida’s launch film and original introduction.
TypeSafe announces public access to Jev without a waiting list. The official console is the starting point for trying typed decisions in your own application.
TypeSafe highlights Jev’s typed-output approach: applications provide state and questions, then act on probabilities, choices or scores. The linked announcement also covers the Venice API integration.
Start with the Launch Post. Explore four official signals.
16 resources
AI-assisted summaries and translations. Check original sources for context and performance claims.
A stock evaluation tool using Jev for fast market analysis.
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A community post describes using Jev to analyze news for stock investment opportunities.
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A community post describing an SEO audit using Jev to analyze website internal links in 45 seconds.
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An experimental trading system using defined rules and Jev for decision-making.
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An AI-driven hedge fund utilizing Jev for fast and cost-effective trading decisions.
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A trading bot using Jev to decide buy/sell actions based on asset price feeds and executing real trades.
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Jev rapidly analyzes 700 live ads in 40 seconds for marketing insights at low cost.
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Jev on Sol. A community post describing an experiment where Jev analyzes Solana blockchain data in real time.
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A community tool leverages Jev to identify relevant X discussions for business outreach.
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A demonstration where Jev was given $10,000 to trade.
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Jev conducts a sentiment-based stock market analysis for the Danish market in 2025, using diverse data sources with low cost.
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Jev identifies and manages marketing messages in Android notifications without content deletion.
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Jev rapidly analyzes competitor ads with detailed classification and cost efficiency.
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Jev rapidly analyzed news articles to suggest relevant stories for brands at a low cost.
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Orus uses Jev to review and approve trade strategies before execution, enhancing decision-making with structured answers.
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Jev trades 15-minute and 1-hour BTC, ETH, and SOL markets on Kalshi.
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