Crowd Analyzer closes $3.5 million Series A with participation from Wamda
SOURCE: Wamda
Dubai-based data intelligence provider and Arabic-focused social media monitoring platform, Crowd Analyzer, announced today that it has raised over $3.5 million in Series A funding from venture capital firms based in the UAE, Saudi Arabia and Kuwait. The funding from investors, led by TechInvest, include Wamda Capital, Arzan VC, Faith Capital and Daring Capital, will enable Crowd Analyzer to enhance and augment the technology behind the platform and support further expansion of its operations in the Middle East and North Africa (Mena) region.
Crowd Analyzer is focused on analysing publicly available data from social media platforms and news websites to provide up-to-date insights to clients who want to stay ahead of trends and digital conversations. Since inception in 2014, it has raised a total of $5.09 million in funding.
The Series A funding secured by Crowd Analyzer will accelerate the platform’s AI and machine learning capabilities in its efforts to further establish itself as a market leader for social media monitoring in the Mena region. Meanwhile, commercially, the funds will expand its presence in Saudi Arabia and Egypt, as well as some of the smaller GCC markets. In addition, the funds will also be used to recruit Saudi local talent.
“As the first Arabic-focused social media monitoring platform, Crowd Analyzer continues to offer indispensable intelligence to companies and brands in the region, helping them to know, understand and access their consumer base quicker and easier than ever before,” said Ahmed Saad, co-founder and chief executive officer at Crowd Analyzer. “By the end of the Series A funding cycle, we now have three of the five investors involved working directly with us. Through this latest round of fundraising, they have recognised our growth and potential.”
Crowd Analyzer specialises in Arabic-focused social media monitoring, analysing content and conversations for sentiment, relevance and Arabic dialect using artificial intelligence, proprietary machine learning and natural language processing.