Technological disruption is currently driving compelling yet complex investment opportunities across robotics, artificial intelligence, and healthcare technology. The indexes are constructed based on fundamental and industry research by a team of financial and industry experts.

    Team of Experts

    Our coverage team incorporates full-time financial and research professionals supported by industry entrepreneurs and academic leaders who specialize in global developments across disruptive tech. Our strategic advisory board includes PhDs and respected tech visionaries.


    Our team established an index methodology and classification system that provides diversified exposure to disruptive technologies. Our ETFs are built to minimize risk by limiting reliance on largest-cap players and to capture the potential growth of global, developing technology companies.


    Our ETFs are constructed based on fundamental and industry research. Our team conducts deep research, working to identify new trends, understand new innovations, and explore every company on the radar -- regardless of size, market cap, or technology.

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    By Bill Studebaker, CIO & President, ROBO Global 

    By Jeremie Capron, Director of Research, Zeno Mercer, Research Analyst, and Bill Studebaker, CIO &...

    By Bill Studebaker, CIO & President, ROBO Global 

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    Healthcare Innovation From An Investor's Perspective

    The convergence of robotics, machine intelligence, and life sciences is enabling breakthrough advancements that touch every aspect of healthcare. While the list of innovations is vast, these technologies are still in their earliest stages. The emerging winners of this disruption will be those companies that are able to effectively deploy innovations such as genomics, precision medicine, or robotics, automation, and AI (RAAI) to improve the quality of care while reducing costs.

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    The How & Why of Investing in AI

    AI is a critical theme for future-focused investing. The simulation of human intelligence processes by computer systems, AI uses machine learning and deep learning to enable systems to learn by themselves with little to no human intervention. And while machine intelligence has been around since the 1950s, it has recently hit an inflection point, moving from the experimental phase to an era of practical commercial application.

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