
The AI feedback platform, built by two ex-Alexa product managers, folds support tickets, app reviews and social posts into patterns teams can act on. Microsoft, Lyft and Perplexity are paying to skip the guesswork.
The Santa Barbara startup, built by two Amazon Alexa veterans, uses AI to read the reviews, tweets, and support tickets your product team never gets to - and tells them what to build next.
Traditional contact center QA reviews roughly 2% of calls and reports the result as if it describes the whole operation. This page frames the choice between sampling and reading 100% of conversations as an architectural decision rather than a feature difference, comparing how CallMiner, NICE Nexidia, Qualtrics XM Discover, and Spiral by UJET handle coverage, discovery of unknown issues, setup time, and whether output reaches a product team or stops at a QA scorecard. The core argument: a 2% sample tells you about your scorecard, not about your customers.