Revuloop clusters every open-text answer into themes with exact counts, scores sentiment on every response, and answers your questions with cited quotes , no manual tagging, no CSV exports, no guessing.
Scores tell you what happened. The comment box tells you why. But most teams either skim a handful of quotes or export to a spreadsheet that dies in a folder.
Theme extraction, sentiment, cited answers, summaries, privacy, and import: one pipeline from raw verbatims to a report you can defend.
Every open-text answer is embedded and clustered, not sampled. Themes come back with exact frequencies, percent of responses, and representative quotes.
Each response is sentiment-scored automatically, then trended over time (improving, declining, stable, or volatile) by day, week, or month.
Ask 'what do detractors complain about most?' in plain language. Answers are grounded in your actual verbatims, with citations to the exact quotes.
A background analysis pipeline turns thousands of comments into findings, root causes, and recommendations: ready by the time the survey closes.
Names, emails, and phone numbers are redacted from verbatims before analysis, so open-text insight doesn't come at the cost of respondent privacy.
Import historical responses from legacy platforms like Delighted or Qualtrics, or bulk-upload via API, and run the same theme analysis on day one.
Most text-analysis tools hand your comments to an LLM and hope. Revuloop computes the numbers in code and uses AI only where it's strong, naming themes and writing summaries.
Theme sizes are computed in code over the full dataset. AI names the themes. It never gets to guess how big they are, so counts stay honest.
Theme clustering covers all completed responses' text answers. A theme mentioned 412 times shows up as 412. Whether you have 100 responses or 10,000.
Every theme and every AI answer links back to real quotes. When you tell leadership 'onboarding is the top complaint,' the receipts are attached.
Filter verbatims by NPS bucket, sentiment, tags, or segment. 'detractors mentioning pricing' is one query, not an afternoon in spreadsheets.
Adaptive AI follow-ups ask 'why?' on every response, so the open text you analyze is interview-depth, not one-line comments.
Wire themes into the closed loop: auto-open a case for every detractor, trigger alerts on sentiment drops, and track resolution to done.
Start free with 200 AI tokens, or import feedback you already have and get themes with exact counts in minutes.
Every text answer is converted into a semantic embedding and clustered with similar answers, producing themes with exact counts, percent of responses, sentiment labels, and representative quotes. AI is used to name and describe each theme, but theme sizes and frequencies are computed in code over the full dataset, so the numbers are exact rather than estimated.
No. Theme extraction, sentiment scoring, and quote selection are fully automatic. You can still add your own tags on top, and auto-tagging rules can apply tags for you as responses arrive.
Theme clustering covers every completed response's text answers. The pipeline is built for surveys from a handful of responses up to tens of thousands. Analysis runs as a background job with live progress, so large surveys don't block your dashboard.
Yes. You can bulk-import historical responses from legacy platforms (such as Delighted or Qualtrics) via the migrations API, or push responses in programmatically. Imported text goes through the same theme and sentiment analysis as native responses.
Three guardrails: theme frequencies are computed in code (the AI only names clusters), conversational answers are grounded in retrieved verbatims with citations to the exact quotes, and numeric claims in answers are validated against the real statistics before you see them.
It's included in Revuloop's plans via bundled AI tokens. Free plan includes 200 one-time tokens, Starter ($19/mo) includes 1,000/mo, Pro ($49/mo) includes 2,500/mo, and Business ($149/mo) includes 7,500/mo. There's also a 14-day free trial of the full Pro feature set with no credit card required.
Yes. Verbatims are PII-redacted (names, emails, phone numbers) before they are embedded and analyzed, and GDPR tooling (consent capture, data export, retention cleanup) is built into the platform.