MARKET RESEARCH

Competitor Patent Filing Alert with Notion Tracker Log

Daily watch for new patent filings from a named list of competitor assignees; logs each new filing as a row in a Notion database and pings Slack only when a watched competitor…

CategoryMarket Research
Enginesim
Difficultyintermediate
Triggerschedule
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerDaily schedule
  • ActionQuery filings per watched competitorPerplexityPerplexity
  • LogicFilter out already-logged filings
  • ActionAppend new filings to Notion trackerNotionNotion
  • LogicAny new filings today?
  • OutputAlert Slack on competitor activitySlack

What it does

It watches a specific list of competitor companies and, each day, finds any new patent filings assigned to them. Every new filing becomes a structured row in a Notion tracker (assignee, title, filing date, abstract, link) and a Slack alert fires only when one of your watched competitors actually files something. No noise on quiet days.

When to use it

Use it when you track a defined competitor set and need an auditable running log of their patent activity, not just a digest. The Notion database becomes a searchable history product can reference in planning.

How it works

  1. 1A daily schedule triggers the run.
  2. 2For each watched assignee, a Perplexity query retrieves recent patent filings tied to that company.
  3. 3A logic filter drops anything already logged (matched against existing Notion rows) and anything older than the lookback window.
  4. 4Each genuinely new filing is appended as a row to the Notion tracker database.
  5. 5A logic branch checks whether any new rows were created today.
  6. 6If yes, a Slack message lists the new filings and links to the Notion rows; if none, the run ends silently.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect PerplexitySearch-grounded answers with citations.
  2. 2
    Connect NotionPages, databases, comments.
  3. 3
    Connect SlackChannels, DMs, threads, mentions.
  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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