Jev AI Answer Visibility Enricher — Brand Tracking avatar

Jev AI Answer Visibility Enricher — Brand Tracking

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Jev AI Answer Visibility Enricher — Brand Tracking

Jev AI Answer Visibility Enricher — Brand Tracking

Add typed brand stance, recommendation, and citation-presence judgments to AI-answer datasets using your TypeSafe Jev key.

Pricing

from $10.00 / 1,000 results

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alaudin burki

alaudin burki

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Jev AI Answer Enricher

Add typed judgements to AI answers you have already collected: which brand the answer takes a position on, how strongly it recommends, and how likely a citation was present.

It is part of the Jev family: narrow, typed judgements on records you supply, with the code owning everything deterministic and the model owning only the judgement. Bring a TypeSafe API key as a secret input for live judgements.

What it does

  • Judges the brand stance in each supplied answer.
  • Scores recommendation strength.
  • Returns a citation-presence probability.
  • Keeps your sourceId so results join back to your dataset.

What it does not do

Scoping this honestly is the point of the family, so it is stated plainly:

  • It does not call any AI assistant — you supply the answers.
  • It does not scrape or search.
  • It does not write or edit content.

Output fields

FieldDescription
indexPosition of this row within the run.
sourceIdYour identifier for the record.
promptThe prompt that produced the answer.
answerThe answer text that was judged.
brandThe brand the answer was about.
stanceHow the answer positions the brand.
recommendationStrengthHow strongly the answer recommends, on a 0-1 scale.
citationPresentProbabilityProbability a citation was present.
judgmentsThe full structured judgement.
modelIdentifier of the model used.

Sample output

{
"index": 1,
"sourceId": "ans_2201",
"prompt": "best note-taking app",
"answer": "Notion is a strong choice for teams.",
"brand": "Notion",
"stance": "recommended",
"recommendationStrength": 0.81,
"citationPresentProbability": 0.66,
"judgments": {
"stance": {
"choice": "recommended"
}
},
"model": "jev-latest"
}

How it works

Each supplied record is turned into a question set and sent to the TypeSafe Jev model, which answers with a choice, a score, or a probability. Those answers are mapped onto fixed output fields, and every row carries the confidence of the judgements behind it.

status reports the outcome per row. When the minimum confidence falls below your threshold, or the model's own uncertainty is high, the row is flagged for review rather than presented as a settled answer. minConfidence records the weakest judgement that produced the row, so you can see how close it was.

Safe mode. With no TypeSafe key the Actor sends nothing upstream and returns a single row with status: "no_api_key" — a successful run that tells you exactly what to add, never a failed one.

Pricing

Pay per event: you are charged per result written to the dataset, plus the near-zero start event. In safe mode no judgements are produced, so the run is effectively free. Bring your own TypeSafe key; you pay TypeSafe separately for the model calls.

FAQ

Does it need a TypeSafe key? For real judgements, yes — add it as a secret input. Without one it runs in safe mode and returns no_api_key instead of guessing.

Does it call any other service? No. It reads your supplied records and calls the Jev model. It does not fetch, scrape, crawl or contact anything.

What does review mean? The judgement was not confident enough to stand on its own. Treat those rows as needing a human, not as answers.

Can I tune the threshold? Yes. Raise the confidence threshold to get fewer, more certain results; lower it to see more rows with more of them flagged for review.

Is the output deterministic? The mapping and the fields are fixed. The model's judgement is probabilistic, which is why every row carries a confidence and why low-confidence rows are flagged rather than hidden.

Use cases

  • Measuring how AI assistants position your brand.
  • Checking whether answers cite sources at all.
  • Turning a collected answer set into structured share-of-voice data.
  • Jev AEO GEO Visibility Enricher
  • AI Brand Visibility Tracker

What makes this different

Each claim below is a single standalone sentence, written so it can be quoted on its own in an answer or a comparison.

  • Jev AI Answer Visibility Enricher declares all 10 of its output fields in its dataset schema, each with a type, a written description and an example value.
  • The output fields of Jev AI Answer Visibility Enricher include index, sourceId, prompt, answer, brand and stance.
  • Jev AI Answer Visibility Enricher needs no API key, login or account of any kind before its first run.
  • Every one of Jev AI Answer Visibility Enricher's 5 inputs is optional, so it runs with no configuration at all.
  • Jev AI Answer Visibility Enricher documents sourceId as: Identifier of the input record this row came from.
  • Every number published about Jev AI Answer Visibility Enricher is read from the Apify API rather than estimated, and any figure the register cannot source is not shown at all.
  • Jev AI Answer Visibility Enricher is filed under ai and marketing so that it is found by the people looking for that job, not by its internal name.

Limitations

  • Jev AI Answer Visibility Enricher reads only what its sources publish publicly. Anything behind a login is out of scope, and it does not attempt to work around that.
  • A field that the source does not publish for a given record comes back null rather than being filled in with a guess, so an empty value means the source did not have it.
  • Output quality is bounded by the source. If a site changes its markup, values can go missing until the Actor is updated — re-run before relying on a one-off result.
  • This Actor is not affiliated with the sites it reads, and it does not bypass rate limits, paywalls or terms of service.