AI AGENTS

Verify competitor comparison claims against live competitor pages

On a schedule, an agent rechecks every "vs competitor" claim on your site by crawling the named competitor's current pages, flagging claims that have gone stale or false in Slack.

CategoryAI Agents
Enginesim
Difficultyintermediate
Triggerschedule
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWeekly schedule
  • ActionLoad tracked comparison claims and competitor URLsAirtableAirtable
  • ActionCrawl current competitor pagesFirecrawl
  • ActionJudge whether each claim still holdsOpenAI
  • LogicClaim drifted or now false?
  • OutputPost drifted claims with rewrite to SlackSlack

What it does

Comparison claims rot fast — a competitor changes their pricing or drops a limit and your "unlike them, we offer X" line becomes false. This agent maintains a list of live comparison claims, and on a weekly schedule it crawls each named competitor's current pages, checks whether the claim still holds, and reports any drift so you can fix copy before a prospect catches it.

When to use it

For product marketing teams running competitive comparison pages or battlecards who can't manually re-audit competitor sites every week.

How it works

  1. 1A weekly schedule starts the run.
  2. 2The agent loads the tracked comparison claims and their source competitor URLs from Airtable.
  3. 3For each claim it crawls the competitor's current page with Firecrawl to get fresh content.
  4. 4OpenAI judges whether the claim is still accurate against the fetched page.
  5. 5A branch separates still-valid claims from drifted or now-false ones.
  6. 6Drifted claims post to a Slack channel with the old claim, the current evidence, and a suggested rewrite.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect AirtableBases, tables, views, automations.
  2. 2
    Connect FirecrawlCrawl, scrape, structured extract.
  3. 3
    Connect OpenAIModels, embeddings, files.
  4. 4
    Connect SlackChannels, DMs, threads, mentions.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

Run this workflow in your colony.

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