AI trend research with real citations
· How it works
Fenfire researches trends from the live web for each brand, keeps the sources attached, and lets your team pin or dismiss what should shape the next brief.
Fenfire trend research uses live web search and keeps the citations with the result. It runs per brand, so the findings can feed a relevant brief instead of becoming a generic list of topics.
A team can refresh the research once per hour for each brand. That keeps the work current without turning every page view into another search job.
The research starts from the brand context held in Fenfire. We use that context to ask a focused question of the public web rather than mixing unrelated workspaces together.
The returned themes include their sources. You can open the evidence and decide whether a claim, conversation, or angle is useful before it reaches a brief.
We store the result with the brand that requested it. Another brand does not inherit the same trend list simply because it belongs to the same team.
Pin the findings that matter. A pinned item stays visible as a deliberate input when the team is deciding what to make next.
Dismiss what does not fit. A passing topic can be real and well sourced while still being wrong for the brand, market, or moment.
Those choices help shape briefs. They do not publish anything and they do not turn a source into an approved brand position.
The live web can change, and a citation can age. Refreshing gives the team a new researched view; it does not rewrite the earlier record or hide where it came from.
We built the feature around a plain standard: show what was researched, show the source, and let the brand team decide what deserves attention.