MARKET RESEARCH

Weekly Opportunity Radar from Brave Search Trend Signals

Every Monday, sweeps Brave Search for your tracked topic queries, clusters the rising results into named themes with an LLM, and posts a ranked opportunity radar to Slack.

CategoryMarket Research
Enginesim
Difficultyintermediate
Triggerschedule
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWeekly cron (Monday 7am)
  • ActionSweep seed queries on Brave Search (past week)BraveBrave Search
  • LogicDedupe and trim result set
  • ActionCluster results into named themes with momentum scoresOpenAI
  • LogicRank clusters and build radar layout
  • OutputPost opportunity radar digest to SlackSlack

What it does

Runs a scheduled sweep across a list of seed queries on Brave Search, collects the freshest results from the past week, and uses an LLM to group them into a handful of named opportunity clusters. Each cluster gets a one-line "why it matters" and a momentum score, then the whole radar lands in a Slack channel as a single digest your team reads over coffee Monday morning.

When to use it

For founders, product marketers, or strategy teams who want a recurring pulse on a market without manually scanning news and forums. Use it when you have 5-20 topics you care about and want them distilled into a few decisions rather than a flood of links.

How it works

  1. 1A weekly cron fires Monday at 7am.
  2. 2For each seed query, Brave Search returns recent web results filtered to the past week.
  3. 3The combined result set is deduped and trimmed.
  4. 4OpenAI clusters the results into named themes, scoring each by signal density and recency.
  5. 5A formatter ranks clusters and builds the radar layout.
  6. 6The digest is posted to Slack with cluster headlines, scores, and source links.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect Brave SearchWeb, news, image, video search.
  2. 2
    Connect OpenAIModels, embeddings, files.
  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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