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Jev AI Apps cases, page 4
213 public posts filed under Apps. English summaries on this page, with a link to each case.
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@rewind02 describes a production app, built with Opus 5.5 and Jev, that takes a URL, screenshots the site with Gemini Flash, has Jev score it against a fixed list of criteria, and ships a shareable report. They say a scan costs fractions of a cent.
built a full production app with opus 5.5 and jev... fed it a url, it screenshots the site, scores it against a list of known patterns, and ships a shareable re…
@miyagawa gives Jev a transcript and show notes so it can judge at what minute and second each link topic appears. They say a 3-hour episode took 0.5s and $0.003.
jev に文字起こしテキストと show notes 渡して、リンクのトピックが文字起こしの何分何秒にでてくるかを判定。3時間のエピソードで 0.5s, $0.003 でできる
@Yarilo7brigada built a feed filter on Jev that asks, for each post, whether it fits their niche, has real value, what format it is, and whether it makes loud claims without proof. They report 20 of 1,000 posts kept, 97ms each, and 1.2 cents for the morning.
98% of my feed is junk. Now I don’t even see it I built a filter that reads my feed for me. It runs on Jev - a model that doesn’t generate text; it just makes b…
@TheStalwart used Jev and @eltokh7’s JSort to re-score the Fedlock corpus: 4,005 FOMC public speeches and statements since the mid-1990s.
Pretty incredible. Just used Jev + @eltokh7's JSort to re-score the entire Fedlock corpus. 4005 FOMC public speeches and statements since the mid 90s. A glimpse…
Quoted @eltokh7
@mmmikhaeel built a tool powered by Jev that extracts any product’s features and business logic into a markdown repo. Enter a product URL and copy features, ICP, messaging, pricing strategy, and so on straight into an md file.
I built a tool powered by Jev that extracts any products features and business logic into a markdown repo Enter a product URL and you can copy features, ICP, me…
@kylejeong built JevSearch: a query and selection criteria go to Browserbase search for the top 25 results, then Jev scores them and returns the top 5. They say Jev often picks URLs outside the initial top 5.
I built JevSearch, search the web & validate your results with Jev. Give a query and selection criteria, use @browserbase search to get the t25 results, then Je…
Quoted @kylejeong
@idleshubh built an in-house review console with Jev to qualify 4,000+ internship applications at tryAlanAI by finding evidence of real work at scale.
JEV is INSANE. 4,000+ people applied for internship at @tryAlanAI. So we built an in house review console to find evidence of real work at scale. Every square i…
@alexchristou_ says years of hoarded Twitter bookmarks are light work for Jev to run through.
Years of twitter bookmark hoarding Light work for Jev to run through
@kensuu was building a site that asks only questions Jev is unsure about, and says the main finding was that questions Jev is barely unsure about are hard to create. They report no other result.
Jevが迷う質問だけをするサイトを作っていたんですが、意外とギリギリ迷う質問というのは難しいという知見が得られただけで、他に何の成果も出ませんでした。
@OmiidSayfun built a Chrome extension because they could not find important unread email. Jev finds those messages and labels them by what they are about. The post links the repo at github.com/iamomiid/jev-inbox.
Couldn't find my important unread emails, so I built a Chrome extension. Jev finds them and labels them by what they're about. You can check it out here: https:…
@nailthy62 describes a Drape experiment: they talk, Jev reads the transcript plus what they are wearing, picks from the closet, and changes the outfit in real time. They report $0.0011 and about 620ms per decision.
jev is insane 🫣 it makes realtime virtual try-on hauls possible. built this experiment for Drape with @typesafeai > i talk > jev reads transcript + what i'm wea…
@TheAIInsiderN built a system with Jev and Opus 5.5 that scores an X post before you publish it. Paste a link, press Start, and get a virality score in minutes; they say the production version took 9 minutes to build. Jev analyzes 800 viral posts as a live baseline, groups them by hook type, runs 12 checks, and finds the 5 most similar posts. Opus 5.5 explains why those posts spread. The result is a score out of 100, estimated likes and views, the share of the baseline the post beats, and a comparison with similar winners. They say it works on drafts too, and the post is tagged #JEV.
JEV + OPUS 5.5 IS INSANE. I built an AI system that analyzes an X post before you publish it. Paste any X link. Press Start. Get a virality score in minutes. Th…
@GitMaxd describes an OSS demo, Agent Seek, where You.com finds pages and TypeSafe Jev re-ranks the results. They report that across 50 questions, 74% preferred the short list over You.com’s order and 86% had the answer in the top 3.
Cool little weekend OSS demo: Agent Seek You .com finds pages. @typesafeai Jev re-ranks the SERP 50 questions: 74% preferred the short list vs You .com order 86…
@frevana_ai says Jev made competitor ad research 30x faster and about 90% cheaper. They typed “game,” and 20 seconds later 294 top TikTok ads across 68 brands were analyzed for about $0.02. Jev pulled the top ads from the past 180 days, scored them on stop-scroll, hook, format, and trust, clustered creative patterns, classified winners, watches, and dogs, built a leaderboard, and recommended what to make next. For gaming they report winning hooks of offer/promo and challenge accepted, and a winning format of gameplay plus UGC. They say this is what they are building at @frevana_ai, with a free link in the first comment.
Jev made competitor ad research 30x faster and ~90% cheaper. Typed “game” as the category. 20 seconds later: 294 top TikTok ads across 68 brands analyzed. Jev:…
@venturetwins says Jev can act as natural-language search on a site, for example scanning thousands of Zillow listings and classifying architecture, renovation status, or freeway proximity. They say one run finished in under 20 seconds and cost $0.18.
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 filte…
@th3nolo is building an agent-agnostic permission gate with Jev and hooks, aiming to work across harnesses that share Claude Code-style hook formats.
Been building an agent-agnostic permission gate: Jev (TypeSafe) + hooks. Many harnesses copy Claude Code's hook format. Some barely have hooks at all. This make…
@irabukht says Jev cut the price of their SEO/GEO audit-and-fix agents by 90%, from about $250, by speeding reads of Search Console, analytics, citation checks, gap analysis, and page fixes. They say it is available in the Ryze AI app and an MCP/Claude connector.
Jev dropped the price of SEO/GEO fixes by 90% Agents that audit and fix a client's SEO/GEO used to cost us ~$250 Here's where the savings come from: 1/ 30x fast…
@phil_dressler demos AI agents in a GTA-style fighter-jet contest: Astra built the sim; Jev drives their decisions.
I put AI agents in a GTA-style fighter jet competition… Astra built it. Jev powers their brains.
@kevindubois tried Jev and open derivatives like Laya inside LangChain4j agentic workflows and reported the wiring felt intuitive.
With all this hype around #Jev and open source derivatives like #Laya I wanted to see how these kinds of decision models would work in Agentic Workflows with #L…
@robj3d3 describes a doomscrolling filter: you pick a niche, Jev reads 3 days of posts and asks 8 questions each, in about 2 seconds for $0.007. It removes bait and hidden ads and judges text plus like, reply, and repost ratios. They say it is free with no signup.
Jev just solved doomscrolling. You pick a niche, Jev reads 3 days of posts and asks 8 questions each. It runs in ~2s for $0.007 😅 > removes bait and hidden ads…
@higgsfield_ai says Jev is good at content filtering and asset selection, and that DeepSeek plus Higgsfield turn the selected assets into ad creatives.
Jev is really good at content filtering and asset selection. DeepSeek + Higgsfield turn the selected assets into ad creatives.
@regalstreak says they gave Jev 5,000 real user journeys and only each user’s first 3 journeys, hiding whether the user returned. In about 10 seconds and for $0.06, Jev predicted who would quit, how confident it was, and where each journey started going wrong.
JEV IS INSANE. We gave it 5000 real user journeys from a consumer app. It only saw each user’s first 3 journeys. We hid whether they ever came back. In around 1…
@hrishioa says Jev models fit data-pipeline work, and that using TypeSafe models for entity resolution cut costs by 99%, stayed within a percentage point of Fable, and raised throughput more than 7x. Prompts and results are linked at southbridge.ai.
Jev models are incredible for data pipeline work. Correctly integrating @typesafeai models for entity resolution cut costs by 99% while coming within a percenta…
@mxfp4 introduces lurk.so, a free product that finds and monitors Reddit threads so they can be cited by AI. They say 4,000 threads were scanned and alerts go to email, Discord, and Slack, made free because of Jev and @getanyapi.
everyone's making demos with Jev but nobody is making real products introducing https://lurk.so find and monitor reddit threads to get cited by AI > FREE > 4000…