In the fast-paced world of asset and wealth management (AWM), fund services providers grapple with an explosion of financial data—from market feeds and portfolio transactions to regulatory filings and client profiles. Yet, much of this data remains siloed and underutilized without inherent context and structure. The semantic layer acts as a vital bridge, infusing raw data with meaning, relationships, and interpretability to drive informed investment decisions and operational efficiency.
Many asset and wealth management firms have modernized data management, integration, quality, and governance—yet the missing link is data connectedness via a semantic layer. The good news: AI and Generative AI (GenAI), including agentic capabilities, can automate this build, unifying structured and unstructured data across public and private sources, creating hierarchies, linking entities, cleaning and filling gaps, and recommending classifications and relationships for rapid deployment.
About the Author
Vladimir Agajanov
Director, Head of Data Science
Vlad is a seasoned leader and solution architect in AI, data science, and machine learning for the financial industry. With diverse expertise spanning generative AI, machine and deep learning, data engineering, product architecture, and operational support, he excels in crafting scalable, robust solutions such as advanced AI tools, marketing analysis models, and risk assessment systems. Leveraging full-fledged product building capabilities with thorough understanding and hands-on experience in every aspect of the product, he is backed by deep education from top schools and extensive resources in AI and related fields.