ABOUT
Elongevity is a founder-led AI transformation consultancy built for small and mid-sized businesses that want practical results without unnecessary complexity.
We combine enterprise-level technical rigor with entrepreneurial speed — helping clients move from a business bottleneck to a working, measurable solution.
Elongevity was founded by Dr. Fei Xing to give SMBs access to the level of AI, data, and transformation expertise that is often available only to large enterprises.
The name “Elongevity” reflects a commitment to enduring business value and long-term growth. Our goal is not to maximize the amount of technology a client uses. It is to become a value-creation partner whose work makes the business more capable, efficient, and resilient over time.
Powered by AI and data-driven innovation, we believe many traditional limits on what a small organization can build, automate, analyze, and improve are disappearing. The opportunity is significant — but only when bold ideas are paired with disciplined execution.
FOUNDER
Dr. Fei Xing
Dr. Fei Xing is a data science and AI leader with more than a decade of experience bridging mathematical rigor and real-world business impact. He holds a Ph.D. in Mathematics and has led analytics, machine learning, digital transformation, and technology initiatives across large organizations, startups, nonprofits, and owner-led businesses.
Before founding Elongevity, Fei served in senior analytics leadership roles, including Director of Analytics, and built and led multidisciplinary teams of more than 90 professionals. His work has spanned strategy, advanced analytics, AI implementation, organizational transformation, and the translation of complex technical ideas into practical operating decisions.
At Elongevity, he brings that same rigor directly into client engagements — working hands-on from diagnosis and solution design through implementation and adoption.
The person helping define the strategy stays close to the implementation and the business outcome.
A lean model reduces the layers between the client, the business problem, and the technical solution.
We can go deep when needed, but complexity must earn its place by creating business value.
We care about whether the solution works in the client’s operating reality — not merely whether the project deliverable is complete.
