Jev for semantic search and reranking

Justine Moore

@venturetwins

Jev can serve as better natural language search on websites. It can scan thousands of Zillow listings and classify properties by things you can't normally filter for - e.g. architecture, renovation status, proximity to freeways. This was done in <20 sec and costs $0.18 👇

Gregor Zunic

@gregpr07

Breaking: Browser Use + Jev = Ultrafast ⚡ Findings flights took 7s and cost only $0.0039 🤯 > new action space every step > DOM state space > small LLM fallback to type (this video is at 1x speed btw) Built a tiny open source browser agent. try it below ↓

Meet Shukla

@meetshukla_

i’m probably going to regret this. 10,000+ videos were imported by our users into Ghostfeed in last 6 months. this weekend, we picked 1,066 reaction videos and analysed all of them with JEV + GEMINI. now you can search by structure, reaction, and who’s on camera. opening the library today which has been our months of data gathering, clone all videos to mass publish them on instagram, tiktok and youtube. comment "reactions" if you want the access to the library.

Stefan

@heystefan_

when a designer gets access to Jev

Aayan

@aaayandev

Jev (@typesafeai) is so insane & cheap for search!! > 6000+ @ycombinator Startups indexed. > Sub 1 second search results. > 90M tokens & $2.7 in total testing costs. Search any startup in a second, in any way! - Color - Niche - Your Competitor - Age - Image - etc... > watch the entire video, it's so freaking cool omg! > this is the coolest thing i have ever built for fun! (worked on it for 2 days straight!)

Zachi

@iam_zachi

I think I just cooked something 🔥 jev(): a PostgreSQL extension that searches your whole database in natural language. No index, no embeddings, just one function. WHERE jev(people, 'could work from home') or WHERE jev(people, 'name sounds european') 129 rows judged in ~1s for $0.0009. Second run: 6ms from cache.

Ian Nuttall

@iannuttall

Cloudflare Workers has Jev now so I'm putting it to the test on keep.md - 7x faster search rerank compared to the current hybrid - 50x faster tagging of content vs GLM 4.7 Flash with no failures

nader dabit

@dabit3

Jev is really good at intent-based search! How it looks in Gmail: (for a huge inbox you'd prob let semantic search / embeddings pull first but still much better experience)

Albiona Hoti

@albicodes

I built a visual reference finder with Jev One single prompt → 100 images from Cosmos, NASA, and The Met my new rabbit hole for creative work 🌻

Marc Köhlbrugge

@marckohlbrugge

Using Jev to filter through my @wip todos It allows me to super quickly find all the instances where I increased revenue, got stuck, switched to a different SaaS provider, etc Things a regular keyword search would never catch

Tamir

@TamirSPIRITT

introducing JevForm, a form that dynamically branches and chooses what to ask next usinng @typesafeai’s Jev in my life i’ve made hundreds of forms with crazy if/then logic. Jev solves it. built with @vercel json-render (by @ctatedev), so theoretically it can support any generative form UI, and @DavidKPiano’s xstate for the actual state Play with it here: https://jevform.spiritt.app/

ギガビット@ゲームつくるひと

@gigabit_million

これGoogle検索でいいのではと思いながら作ってたけど、Chrome拡張機能でJevで意図で検索できるの作ってる人がかなりいたみたいでJevはGoogle検索より良いケースあるみたい。Jevのユースケースとして良いやつだった

げま｜個人開発

@gemama0

Jevでノートの自動タグ付けシステムを作った🎉 Obsidian使っている人はぜひ👇

AYi

@AYi_AInotes

你是不是也在推特收藏了上千个书签，最后只存不看， 开发者 Alex 用jev解决了这个痛点， 他刚上线的这个工具 Margin, 算是真正把你的书签收藏救活了， 以往尝试用传统大模型做个人书签检索, 体验几乎是灾难级的: 把几百条推文全文丢给大模型或者向量库, 每次搜一句话要在云端等上半分钟, 还要硬烧几块钱的调用费, 根本没人愿意天天用。 而接入专做强类型决策的 Jev 之后, 整个检索逻辑彻底被掀翻了。 你只要用扩展把这几年积攒的书签一键导出导入工具, 接下来直接用最口语化的人话去搜, 比如问它有哪些关于冷启动获客的实操技巧。 系统完全不需要自回归逐字生成废话, 而是由底层的决策小脑以单条几十毫秒的速度在后台做并行打分。 短短几秒钟之内, 上百条沉睡了几年的推文被挨个计算出匹配置信度, 界面带着进度条瞬间弹出一份按相关性精准排序的推文清单, 甚至把每条内容到底契合在哪用数字标得清清楚楚。 百万 Token 只要四分钱且输出免单的机制, 让这种以往极度奢侈的遍历打分, 变成了一次只需要花几分钱的日常微小操作。 真正好用的知识库从来不是逼着人类自己去建复杂的分类文件夹, 而是把检索成本压低到可以肆无忌惮地用自然语言反复提问。 以前是把好内容随手扔进黑洞当个数字囤积狂, 从今天起是用毫秒级的决策神经随时把冷数据捞出来变成生产力。 https://x.com/alexchristou_/status/2101674202361221376/video/1

Likit D

@Likitd_

Jev jev jev jev Your RAG pipeline just got a relevance upgrade. excited to introduce jev-ranker — Jev-powered reranking and relevance filtering How much can smarter reranking improve a RAG pipeline? Try : npmjs.com/package/jev-ra… Benchmark Results: