SOCIAL MEDIA
Scan new brand mentions for impersonator handles and open a takedown packet
Scrapes fresh brand mentions across social platforms, scores each posting handle for impersonation and typosquatting against your verified accounts.
How it runs
The automated pipeline, trigger to output.
- TriggerEvery 4 hours
- ActionScrape recent brand mentions and profilesApify
- ActionScore handles for impersonation vs. verified listOpenAI
- LogicKeep only handles above risk threshold
- ActionCapture profile screenshot as evidenceBrowserbase
- OutputOpen Notion takedown packet per flagged handleNotion
What it does
It continuously watches for posts and profiles using your brand name, then separates genuine fans from accounts pretending to be you. Every suspicious handle becomes a ready-to-file Notion takedown packet complete with the offending URL, a captured screenshot, the impersonation signals, and the platform's abuse-report link.
When to use it
Run this when your brand is being impersonated faster than your team can manually report. It is built for trust-and-safety or social leads who need defensible evidence rather than a vague "this looks fake" hunch.
How it works
- 1A schedule fires every few hours.
- 2Apify scrapes recent posts and profiles mentioning the brand across platforms.
- 3An OpenAI scoring step compares each handle, display name, and bio against your verified-account list and rates impersonation risk with reasons.
- 4A logic branch keeps only handles above the risk threshold.
- 5Browserbase captures a full-page screenshot of each flagged profile as evidence.
- 6A Notion takedown packet is created per handle with the evidence, signals, and the correct platform abuse link.
Set it up
What you configure once, before turning it on.
- 1Connect ApifyActors, scrapers, datasets.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect BrowserbaseHeadless browsers, sessions, replays.
- 4Connect NotionPages, databases, comments.
- 5Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 6Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 7Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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Run this workflow in your colony.
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