Scoring OCR parses with Jev
The author notes that a misread table can still look perfectly aligned, so they use Jev to score every MiniCPM-OCR parse from 0 to 1, helping them decide which results to check before the numbers reach a report. Link
THE JEV GUIDE · CURATED EDITION
Data analytics.
Launch news, explanations, demos, and community projects around TypeSafe Jev, organized by topic. Every entry links back to its X source.
Curated selection · Not exhaustive · Updated manually
6757curated posts
3414original videos
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Jev’s Cost Edge: People Data for Less
The post compares people-data costs across ContactOut, Clay Growth, and ZoomInfo, and points to Jev by TypeSafe AI as the obvious choice.
Jev Powers Rapid Safety Report Analysis
We integrated Jev to read the full Safety Report in a fraction of a second and provide plain answers like whether a token will graduate, greatly reducing manual reading effort.
Processing Data with AWK and Jev
A developer shares ongoing work on data processing using AWK and Jev, demonstrating Jev's application in real development scenarios.
Automate app review analysis with Jev
Kike Lopez built a tool where you type any app, and Jev reads its latest 500 reviews and tells you what users complain about most. Link
One card in the feed, every sixteen, on every page of it. $50 a week, cancel any week.
Using Jev for Data Classification
The author uses a large volume of Hansard reports, news archives, and social media posts to construct context and stakeholder profiles, and uses Jev for classification.
OneStar: Analyzing App Reviews with Jev
Jared introduces OneStar, powered by TypeSafe's Jev model, which makes it cheap to ask questions across thousands of app reviews, revealing what users love, why they leave, and what they ask for. Launching on Product Hunt tomorrow.
Jev Router Latency Comparison: 6.18s Median vs DeepSeek V4.1 Flash's 3.64s
The post compares Jev Router's end-to-end request latency with nearby Pareto optimal models. Results show Jev Router's median latency was 6.18 seconds, higher than DeepSeek V4.1 Flash (Max)'s 3.64 seconds, with the gap widening at P90.
Jev Model Call Efficiency Analysis
Arena.ai data shows Jev prioritizes efficiency, routing over a quarter (28.1%) of all model calls to DeepSeek V4.1 Flash, while favoring OpenAI models like GPT-6 Astra over Anthropic's LLMs.
Stanford Professor Builds Data Science System with JEV
The data science system analyzes 40 billion data points every 15 minutes and automatically decides which results require deeper analysis. A Stanford professor spent over a year developing it.
Qwen+Jev Layered SQL Security Architecture
The article analyzes an AI data analyst setup: Qwen generates SQL, Jev reviews it, and code decides what can run. Key rule: anything that can be code-checked should be code-checked. Link
Built an X viral post viewer with Grok 4.7 + Jev
The author built an X viral post viewer with Grok 4.7 and Jev: Jev handles scoring/sorting, Grok 4.7 explains. They claim it processed more posts in 31 seconds than they did all year, for less than a bus ticket.
