Scanning 50,000 conversations in 20 seconds, finding 151 backlink forums, and building a placement calendar
Jev Content Marketing Demos
See 180 real Jev demos showing how it handles social-content evaluation, copy decisions, and growth workflows, with videos and the original posts.
Classifying TikTok clips in about 70 ms to repost likely viral videos and skip the rest
Evaluating every visible X post with 12 typed questions and returning keep, reply, skip, or mute decisions
Searching Twitter bookmarks by meaning to return more relevant saved posts than keyword matching
Choosing whether to use a sub-agent, ask a person, stop retrying, or reuse cache before costly Picsart generation
Assembling prepared colors, copy, design, and layout parts from audience attributes without regenerating everything
Turning storyboard text into selectable camera, character, position, and pose variables, then validating the generated video
Estimating whether an X account can reach creator revenue in 90 days and scoring strategy, efficiency, and remaining distance
Searching 100+ posts per profile, identifying the creator's niche, and ranking them among leading voices
Triaging 3,412 posts with eight bots and turning the results into a seven-day content plan in 13 seconds
Reading 700 competitor ads in 41 seconds, gating outgoing posts, and sorting 800 DMs before the app opens
Filtering 100 arXiv candidates with one yes-or-no question per paper, removing off-topic cards in about one second
Returning pick-one, rating, and yes-or-no probabilities for creator decisions in about 300 milliseconds
Reading 384 morning-news items and selecting relevant stories for 15 brands in 24.9 seconds for $0.19
Turning a Breaking Bad meme into a structured Memova page through a short sequence of follow-up questions
Scoring whether content is worth reading and applying a temporary blur when the result says to ignore it
Matching a free-text request to the most relevant meme in an indexed collection
Judging 12,418 Google Ads search terms in 12 seconds, finding 1,206 negatives and flagging $3,912 in waste
Classifying X and YouTube posts as skip or for-you from a user-defined content preference
Scanning website content against predefined SEO schemas and identifying changes that raised visibility scores by more than 15%
Selecting context-aware GIFs and emoji from 1,300+ items in about 250 ms for $0.0003
Classifying 148 long-form WeChat articles by private-domain sales scenarios in under two minutes
Sorting a collection of cat memes into useful categories through typed judgments
Deciding whether each Picsart campaign stage should run, retry, reuse cache, or ask a person before expensive generation
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