CleverX · AI research analysis
Months of research,
ready to review
in minutes.
Large studies could run for months, leaving researchers to read transcripts and scrub through recordings by hand. We designed AI analysis that generated the first pass: transcripts, summaries and highlight reels, in minutes.
One session with its player, chapters, synced transcript and AI summary.
CleverX supports human-moderated, AI-moderated and unmoderated studies. A single project can contain dozens of recordings, each fifteen minutes to an hour long. Once fieldwork ended, researchers still had to work through that material one recording at a time.
Researchers used the feature to speed up synthesis. Founders and PMs could use the same project view to read a study themselves instead of waiting for a separate report.
01 · the starting point
Why analysis took so long
Researchers had to read transcripts, jump through recordings, tag useful moments and remember how one session connected to another. On larger studies, analysis could continue for months after the research began.
The volume grew faster with AI-moderated studies. Researchers could run far more interviews, but the old analysis process still asked them to review each one manually.
02 · the first pass
AI organised the study before anyone opened it
When a study finished, the platform generated transcripts, chapters, summaries, themes and suggested highlights. Researchers no longer had to begin with a blank set of recordings; they could review an organised first pass in minutes.
AI chat let people ask follow-up questions across the study, including whether anyone disagreed or what appeared in a specific part of the research. They could keep a useful answer as a finding or continue the thread.
Ask AI could answer follow-up questions across the project.
03 · review
From a finding to the recording
AI chapters gave each recording a table of contents, so a researcher could jump to the relevant section instead of scrubbing from the beginning.
Each AI summary or suggested highlight linked to the participant and timestamp it came from. A researcher could jump to that moment, check what was said, then keep, edit or discard the suggestion.
The transcript stayed in sync with playback. Selecting a line opened the actions researchers already needed: highlight, tag, clip, comment or ask the agent.
Selecting a transcript line opens the actions for that moment, including the project’s own tag list.
Saved moments collected into one highlight reel for the project. AI suggestions were marked separately from clips chosen by a researcher.
One highlight reel, drawn from every session in the project.
04 · the summary
Insights that can be reviewed one by one
Instead of generating one long summary, we broke it into individual insights. A researcher could keep, edit, tag or discard each one without touching the rest.
The project summary is split into individual insights that can be reviewed separately.
05 · outcome