Jev Bulk Classifier — Text & Image Labels, Ratings, Yes/No
Pricing
$2.00 / 1,000 evaluated texts
Classify, score and flag texts or images — tickets, reviews, leads, product photos — against your own labels, with one typed answer and confidence per row.
The texts to evaluate — one per line. Leave empty if you are reading from an existing dataset instead.
Images to evaluate — one URL per line, each evaluated on its own. JPEG, PNG, WebP and GIF work; large images are resized automatically.
Evaluate the records of an existing dataset instead of the texts above — pick a dataset or paste the dataset ID from any previous run, e.g. the output of a scraper.
When reading from a dataset, only send these fields to the model, e.g. 'text' and 'title'. Leave empty to send the whole record.
When reading from a dataset, the fields that hold image URLs (a URL or a list of URLs), e.g. 'displayUrl' or 'images'. Those images are evaluated together with the record's text.
The questions to ask about every text. Each question has a 'key' (the output column name), a 'type' ('choice' picks one option, 'score' rates against ordered levels, 'noul' answers yes/no), 'instructions', and 'criteria' (options for choice, ordered levels for score).
Maximum number of texts to evaluate in this run. Set 0 for no limit.
How many texts to evaluate in parallel. Higher is faster; lower it if you hit rate limits.
