With Qrvey, you really can have it all... a great product from a
company and a buying experience that works with you, instead of against you, and will meet your
needs today as well as tomorrow. Qrvey platform provides the best self-service data and
experience available today and is fully embeddable to provide analysis and automation anywhere
The Qrvey team has decades of experience in the analytics &
intelligence industry and brings with it a unique understanding of what our customers need and
ability to turn those needs into reality.
Finally, there’s the way Qrvey does business. We believe in a
no-pressure sales approach with transparent pricing, flexible licensing and free trials to make
Qrvey is right for you before you buy.
Modernize Your Embedded Analytics.
Learn why Product Managers love Qrvey
A Unique Deployment Approach
Many products can be deployed to the cloud, but
that doesn’t mean they’re taking advantage of everything the cloud has to offer, or that they
provide the features your company requires, like control and data security. But Qrvey is
Qrvey is not a SaaS offering, nor are we
software that can be hosted in the cloud. We uniquely deploy into your own AWS cloud account,
you’re always in control of your installation and your data. And we are also cloud-native,
full advantage of powerful cloud services like Elasticsearch, S3, DynamoDB, Kinesis, Lamba and
dozens more. No other analytics solution can come close to the power and scalability of Qrvey.
Learn even more about Qrvey’s Unique Cloud Deployment Model
What You Get With Qrvey
Qrvey empowers everyday business users with world-class, self-service data tools.
A single, unified platform for data collection, analysis and workflow automation.
All Data Analyzed
Structured, semi- and unstructured data with files, images, audio, video and more.
Embed any portion of the Qrvey platform into other web or mobile applications.
Built in the cloud with microservices that are fast, functional, lightweight and
Industry-leading performance that scales effortlessly for the most demanding workloads.