
FUNDSaiQ is a next-generation wealth tech platform for financial advisors, powered by AI and machine learning. It helps users find and monitor the best fund managers, focusing on both financial performance and ESG criteria. The platform aims to fill a gap in the market by providing a comprehensive hub for identifying top fund management teams, monitoring their performance, and tracking relevant news, with no other generally available platform offering the same capabilities. Their team comprises individuals with extensive experience from leading financial institutions like Citi, Goldman Sachs, and Morgan Stanley, combined with technology development expertise. FUNDSaiQ is disruptive to the wealth management industry, offering an unbiased and independent approach to fund selection and monitoring.

FUNDSaiQ is a next-generation wealth tech platform for financial advisors, powered by AI and machine learning. It helps users find and monitor the best fund managers, focusing on both financial performance and ESG criteria. The platform aims to fill a gap in the market by providing a comprehensive hub for identifying top fund management teams, monitoring their performance, and tracking relevant news, with no other generally available platform offering the same capabilities. Their team comprises individuals with extensive experience from leading financial institutions like Citi, Goldman Sachs, and Morgan Stanley, combined with technology development expertise. FUNDSaiQ is disruptive to the wealth management industry, offering an unbiased and independent approach to fund selection and monitoring.
Sector: Wealthtech (AI/ML fund selection & monitoring)
HQ / Focus: UK-based; platform for financial advisors and IFAs
Founders: Tashfin Shafique (CEO) and Mizan Rahman (CTO)
Data partners: Refinitiv and Morningstar (cited as data suppliers)
Team size: Approximately 8 employees
Fund selection and monitoring for wealth managers and financial advisers, emphasizing active manager outperformance and ESG screening.
Financial technology
Total Funding: 0.00 USD