AI AGENTS

Verify press release claims and quotes before distribution

When a press release draft is opened in a review channel, an agent checks every factual claim and attributed third-party quote against sources.

CategoryAI Agents
Enginepaperclip
Difficultyadvanced
Triggerevent
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerDraft posted in PR review Slack channelSlack
  • ActionSplit into claims and attributed quotesOpenAI
  • ActionFind authoritative sources for each itemPerplexityPerplexity
  • ActionScore Verified / Unverifiable / MisattributedOpenAI
  • LogicAnything unverifiable or misattributed?
  • OutputReply with release/hold decision and risk listSlack

What it does

Press releases carry the highest reputational and legal stakes of any marketing copy, and they often cite analyst figures, awards, and partner quotes that must be exactly right. This agent reviews a draft on demand: it verifies each factual claim against primary sources, confirms every attributed quote or third-party figure traces to a real, citable origin, and returns a clear release-or-hold decision with the specific risk on each flagged line.

When to use it

For comms and PR teams who need a rigorous, fast final check on a release before it goes to the wire or to a journalist.

How it works

  1. 1A reviewer posts the draft in a designated Slack channel to trigger the run.
  2. 2OpenAI separates the draft into factual claims and attributed quotes or third-party figures.
  3. 3The agent searches Perplexity for authoritative sources backing each item.
  4. 4It scores every item Verified, Unverifiable, or Misattributed with a citation.
  5. 5A branch sets the overall decision to Release only if nothing is unverifiable or misattributed.
  6. 6A threaded Slack reply returns the decision plus a line-by-line risk list.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect SlackChannels, DMs, threads, mentions.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect PerplexitySearch-grounded answers with citations.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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