We started as a Contact Center QA company that powers human-QA workflows in 2017.
The arrival of LLMs transformed the potential to turn the conversation data in our platform into structured data.
As a result, CEOs and their leadership team's eyes opened to the potential for insights from conversation data to drive strategic priorities.
This opened the window of not only helping QA teams analyze conversations but also every person in a company.
It required our product to transform from a workflow solution to a data platform - and our experience working with 500+ Quality Teams, their tech stacks, and their use cases was mission-critical to how we designed our platform to work for small and large teams - and folks both within and outside the Contact Center.
We are building the #1 place to analyze conversation data.
Modern QA and VOC start with a Conversation Data Platform



Business-critical use cases
Identify non-compliant interactions in real time, reducing risk and ensuring regulatory compliance across your operations.
Use AI insights to uncover missed sales, optimize upsell and cross-sell strategies, and drive higher revenue potential.
Detect churn early by analyzing sentiment and friction points to intervene and improve retention before escalation.
Optimize chatbot performance by analyzing interactions and sentiment to improve workflows and self-service experiences.
Monitor and optimize both in-house and outsourced agent performance, ensuring quality, enforcing compliance, and providing feedback to align with brand standards.
Transform unstructured data into actionable insights, analyzing customer sentiment to improve service strategies and deliver exceptional experiences.