Singapore-headquartered Mozark has successfully raised $40 million in Series B funding to bolster its global footprint.
The funding round was led by the International Finance Corporation (IFC) and RMB Capitalworks, with existing investor Kalaari Capital also participating.
Mozark's Cutting-Edge Testing Platform
Mozark specializes in digital experience testing and measurement, conducting real-world simulations of user journeys across diverse devices, networks, and locations.
Its innovative technology produces synthetic telemetry data, enabling organizations to detect and resolve performance bottlenecks in applications, AI systems, and supporting infrastructure like data centers and networks.
Founded to address the complexities of modern digital services, Mozark has grown to serve over 50 enterprise and government clients across more than 20 countries.
The platform operates on thousands of live devices simultaneously and has already executed over 25 million tests, demonstrating robust scalability and reliability.
Strategic Plans for Growth and Innovation
With the fresh capital, Mozark aims to drive expansion into key markets including the United States and regions in the Global South, alongside pursuing potential strategic acquisitions.
The company will enhance its testing capabilities for applications, networks, and AI infrastructure to meet surging enterprise demands.
Additionally, Mozark plans to fast-track the commercialization of its specialized platform for agent-to-agent communication systems.
Broader Impact in the AI Era
As artificial intelligence accelerates application deployment across consumer, enterprise, and public sectors, the need for reliable performance measurement has never been greater.
Mozark's co-CEOs Kartik Raja and Fabien Renaudineau emphasized that organizations require tools to gauge digital services in real-world conditions amid global AI expansion.
This funding positions Mozark as a pivotal player in ensuring equitable digital access worldwide, promising significant advancements in performance optimization.