Semarize

Companies that run sales calls, customer support conversations, and hiring interviews generate valuable signals inside those conversations, things like whether a champion is confirmed, whether budget is confirmed, whether a customer showed churn intent, or whether an interviewer asked structured competency questions. Today teams reviewing these conversations have to manually listen or read transcripts and infer these signals themselves, which is slow and inconsistent across reps, agents, and interviewers. The page's own sample output lists competitor mentions such as Gong and Chorus, suggesting Semarize is positioned against existing call intelligence tools in the sales space and against manual review in support and HR contexts. Without a structured extraction layer, teams lose time reconciling scattered notes and cannot systematically track things like objection categories, compliance scores, or flight risk signals across many conversations.

Semarize is described as a Conversational Intelligence API, with a site structure built around Product, Solutions, Pricing, and Developers sections and a 'Start building' call to action, indicating it is sold as an API for other companies to integrate rather than a standalone dashboard product. The sample output on the page shows it extracting dozens of named, structured fields from conversation transcripts, including sales qualification data like MEDDICC Score, Champion Confirmed, Decision Criteria Explored, and Competition Mentioned, customer support fields like Churn Intent, Agent Empathy Score, Compliance Score, and Save Offer Made, and hiring and HR fields like Competency Score, Bias Indicator, STAR Response Quality, and Flight Risk Signal. This suggests the API is built to serve multiple use cases, sales call analysis, support QA, and recruiting or exit interviews, from a shared underlying extraction engine, returning quantified scores (for example Deal Health Index, Sentiment Score, Talk Ratio) alongside boolean and categorical flags that developers can consume programmatically.