Posting peluncuran Jev
Diogo Almeida memperkenalkan Jev, model keputusan terstruktur dari TypeSafe. Tonton film peluncuran dan eksplorasi thread asli untuk pendekatan model, contoh, dan kinerja yang dilaporkan penulis.
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Recent activityA FIELD GUIDE TO JEV / VOL. 01
Yang terbaik dari Jev: proyek nyata, panduan praktis, dan ide dari seluruh internet.
Diogo Almeida memperkenalkan Jev, model keputusan terstruktur dari TypeSafe. Tonton film peluncuran dan eksplorasi thread asli untuk pendekatan model, contoh, dan kinerja yang dilaporkan penulis.
Pengumuman peluncuran resmi TypeSafe memperkenalkan laboratorium dan mengarahkan pengembang ke Jev. Termasuk film peluncuran Diogo Almeida dan pengantar asli.
TypeSafe mengumumkan akses publik ke Jev tanpa daftar tunggu. Konsol resmi adalah titik awal untuk mencoba keputusan bertipe dalam aplikasi Anda sendiri.
TypeSafe menyoroti pendekatan Jev untuk output bertipe: aplikasi menyediakan state dan pertanyaan, lalu bertindak berdasarkan probabilitas, pilihan, atau skor. Pengumuman terkait juga mencakup integrasi API Venice.
Start with the Launch Post. Explore four official signals.
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AI-assisted summaries and translations. Check original sources for context and performance claims.
Klasifier yang menilai kesulitan prompt secara real-time, memungkinkan mode cepat untuk prompt sederhana untuk meningkatkan interaksi pengguna.
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Demo yang menunjukkan Jev memilih model AI paling sesuai untuk tugas generasi video dan gambar di Higgsfield.
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A guide explaining Jev's approach to making typed decisions rather than processing text.
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A GitHub Action using Jev for automated PR triage and classification.
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A tool that scores video ad shots in 1.5 seconds using Maxfusion and Jev, processing over 450 ads in under three minutes.
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A demonstration of Jev's capability to quickly categorize a large volume of Hacker News posts.
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Jev enables natural language search for Zillow listings, classifying properties by non-standard filters.
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A demo showing how to make open source models behave like Jev using inference engineering and scoring endpoints for decision-making.
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An image classifier using OCR and Jev processes 900 images in 40 seconds.
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A community post presents a codebase complexity classifier using Jev, aiming to address overengineered code.
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DuckDB extension that classifies rows in CSV, Parquet, or DuckDB tables with Jev, about 10 seconds per 1,000 rows.
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Jev is utilized for decision-making processes on Cloudflare, including support routing and risk management.
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A task using Jev to score 3,000 kids' snacks with multiple criteria in 28 seconds.
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Jev classifies 500 emails quickly and inexpensively, demonstrating its efficiency in processing tasks.
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Jev demonstrated over 5x faster performance than other models in testing.
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Jev evaluates the pacing of a frontier-AI essay written by @DarioAmodei.
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Real-time Discord moderation bot: Jev evaluates messages and metadata in parallel to catch phishing, spam, and social engineering with a progressive escalation ladder.
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Jev is demonstrated as a classification model with practical examples.

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A GitHub project routing tasks by selecting model tier, tools, skill, and effort.
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A community post about using Jev for incident triage in Box, returning boolean results with probabilities.
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Uses Jev to decide which AI model to use before generating output, based on prompt and quality requirements.
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GitHub project for content moderation with category-specific probability thresholds. Enables automated content filtering.
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A Jev-powered system that analyzes PDFs page by page to determine which require OCR processing.
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Jev enables flexible, type-safe classification as a fundamental programming primitive.
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A GitHub project that uses Jev to triage and route posts from the live Bluesky firehose with human oversight.
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Fast CVSS scoring from vulnerability descriptions using Typesafe Jev.
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Pre-alpha PostgreSQL extension for TypeSafe AI (Jev) categorical classification.
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A community post detailing a dashboard that classifies X posts across eight dimensions using Jev for content research.
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Self-hosted AI email classifier for Gmail powered by Jev. Create custom labels, organize your inbox, and filter spam with confidence and cost controls.
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SuperX yang terintegrasi dengan Jev memungkinkan pemeringkatan pos yang cepat, menganalisis 61 pertanyaan per pos dalam waktu kurang dari satu detik dengan akurasi prediksi potensi viral yang tinggi.
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Short practical intro with a Python ticket-triage example.
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A project using Jev for skill routing in an agent system, based on community development.
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A 26-sheet construction plan set was classified in 2.9 seconds using Jev with an LLM pipeline, costing $0.0052 and matching GPT-4.1 and GPT-6 Astra performance.
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PulseLane — clinic triage decisions via TypeSafe Jev.
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Classifies tax documents using an LLM pipeline for efficient processing.
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Near-real-time scoring of TikTok and Instagram hooks against about 100 personas.
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Analyzes 100,000 X posts in 20.4 seconds using 14 yes/no questions per post for viral potential assessment.
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A system tested on 1,500 emails for classification effectiveness. Demonstrates potential for automated email management.
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Diffusion-style pixel art out of a classifier: 256 parallel per-pixel Jev questions plus refinement passes.
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A developer project exploring decisions using a classifier as a next-token predictor.
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A real-time computer assistant using Jev and local Whisper to process voice input, classify actions, and interact with the screen through a Swift app for accessibility.
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An ad blocker extension using AI for real-time classification and removal of ads.
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Open-source Jev log triage for OpenTelemetry. Score the signal before expensive LLM analysis.
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Matched-precision comparison against a private fine-tuned classifier.
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Runnable Jev examples through OpenRouter for immediate implementation.
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Classify Git commit diffs and messages with Jev. Bug fixes, security fixes/CWEs, and change types.
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Marketing analytics platform whose feature flag routes brand-visibility classifiers off an LLM and onto Jev boolean decisions.
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1,800-point thread debating whether typed decisions replace LLM calls for classification, routing, and scoring.
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Async LangGraph workflow that gets a typed Jev Choice (invoice or general) and routes each inbound email to the matching handler.
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An open-source project that helps select relevant Claude Code skills by prioritizing frequently used ones through Jev integration.
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A prototype that classifies symptoms and updates diagnoses using medical ontologies during live clinical consultations.
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A LangChain package with TypeSafeClassifier for integrating Jev into applications.
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Typesafe.ai System One Model Jev navigating a Neo4j graph by using a classifier over neighbouring relationships.
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Jev is a System One model on OpenRouter that provides decisions with probabilities.
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Helper n8n community node for Jev by TypeSafe. Classify, route, and score text with questions you define, and get a probability for every answer so unsure items can go to review.
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Jev enables Grok Bot to control real Chrome for faster, automated tasks instead of slow look-and-click methods.
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Open-source AI email triage for Gmail. Sorts your inbox into Needs reply, Updates, Promos, Sales and Spam with Jev, TypeSafe AI's decision model, via Vercel AI Gateway. Read-only, runs locally, 1,000 emails in about a minute for 3 cents.
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A setup where Jev selects between different AI models for specific tasks, streamlining model usage in a single terminal.

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JEV Document Classification enables the rapid and cost-effective classification of text-based documents using AI, leveraging TypeSafe's "System One" model.
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A guide on using Jev to route between models and block risky tool calls.
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Benchmarking TypeSafe's Jev decision model as a cost-efficient LLM router on RouterArena.
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A resource detailing a test of Jev on 12 real-world scenarios, including speed, cost, and practical applications.

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A community example demonstrating how Jev can classify company invoices into accounting categories rapidly.
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A project classifying 1,018 AI research papers using Jev, achieving low cost and fast processing for organizing academic work.
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Autonomous System-One Triage Engine & Benchmark powered by TypeSafe AI (Jev). 75ms inference, $0 output tokens, and RLCD epistemic safety gates.
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Open-source Jev-style System One decision model. Gemma 3 270M with a scoring head — fast, calibrated decisions in a single forward pass. No text generation. Inspired by TypeSafe.ai's Jev.
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A GitHub project for a Pareto-optimal OpenRouter router for Pi, decided by Jev.
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Comment-moderation playground: paste a comment, Jev decides what to do with it.
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LaneBreak — support ticket priority+routing via TypeSafe Jev.
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Experimental semantic line search with TypeSafe Jev via OpenRouter. Python CLI with no runtime dependencies.
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Guardrails for LLM apps in one API call. Prompt injection, jailbreaks, leaks, unsafe content. Built on TypeSafe Jev. MIT.
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Neon Function proxy for the Neon AI Gateway with TypeSafe Jev routing.
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