Qrvey

About Qrvey

Qrvey offers a specialized embedded analytics platform developed for Software-as-a-Service (SaaS) companies. Founded in 2015 by Arman Eshraghi, a serial entrepreneur with over 25 years in the software industry, the company was established to address the limitations of traditional analytics. Eshraghi's background includes founding Logi Analytics and two other software firms, providing him with deep insights into product development and B2B software needs. The founding team, many of whom worked together at a previous pioneering web-based business intelligence company, reunited to create Qrvey, aiming to spearhead the next technological shift toward cloud-native analytics. The company secured its first seed funding of $1.2 million in 2016, led by the Center for Innovative Technology. Subsequent funding includes a $7.5 million Series A round in May 2020 and an additional $8.5 million investment in February 2021, bringing its total funding to $19.5 million.

The company’s core business is providing an all-in-one analytics solution that allows SaaS vendors to integrate data analytics directly into their applications. This enables their clients to offer robust, self-service reporting and data visualization experiences to their own customers. The business model involves licensing its platform, which is deployed directly into the client's own AWS cloud environment rather than operating as a separate SaaS product. This self-hosted approach ensures that a client's data remains within their own infrastructure, addressing critical security and compliance requirements. Qrvey's target market consists of SaaS companies of all sizes, from startups to large enterprises, across various industries including AdTech, cybersecurity, finance, and healthcare.

Qrvey's platform is a full-stack solution designed to minimize development time and costs for its clients. It includes a multi-tenant data lake with Elasticsearch as the analytics engine, a unified data pipeline for ingesting and transforming various data types, and a semantic layer for managing data security and user access. Key features for end-users include dynamic dashboards, customizable reports, user-level personalization, and data-driven workflow automation. The platform is fully white-labeled, allowing SaaS companies to match the analytics interface seamlessly with their application's branding. A significant differentiator is its purpose-built architecture for multi-tenant SaaS environments, which contrasts with many legacy BI tools designed for general enterprise use. This architecture, combined with a usage-based pricing model, offers a cost-effective and scalable solution for growing SaaS businesses.