Advait Jayant is a researcher and technology executive active in the fields of artificial intelligence, digital assets, and financial systems. He is the Chief Strategy Officer of OpenGradient, focusing on data-driven markets, decentralized technology, and AI infrastructure. [1] [2]
Jayant completed his undergraduate studies at Birla Institute of Technology and Science, Pilani, earning a first-class honors bachelor’s degree in computer science. He later pursued graduate studies at London Business School, completing a Master of Science in Analytics and Management and a Master of Research in Capital Markets, both with distinction. He subsequently began a Doctor of Philosophy (PhD) program at London Business School, focusing on cryptocurrency markets under the supervision of Professor Alastair Lawrence. His doctoral work has included research on trading behavior in digital asset markets, including analysis of wash trading in non-fungible token markets. [3]
Jayant began his career in research-focused roles in London, working at IMMO from 2020 to 2021, where he contributed to data-driven real estate investment and portfolio development. He later joined Fabric Ventures as a Research Partner from 2021 to 2022, leading research efforts at a UK-based venture capital fund focused on blockchain and digital assets. During this period, he also served as a MakerDAO delegate for decentralized governance between 2021 and 2022. In parallel, he worked as an author with O'Reilly from 2019 to 2022, producing over 50 publications on artificial intelligence.
In 2022, Jayant took on academic and entrepreneurial roles. He served as a lecturer at UCL from 2022 to 2023, teaching portfolio management. That same year, he founded SuperSight, where he served as Chief Executive Officer until 2024. The company developed tools that integrated on-chain and off-chain data analytics and raised early-stage funding before its intellectual property was acquired. In 2024, he founded Peri Labs and served as Chief Executive Officer until April 2025. The organization focused on artificial intelligence research, including edge computing. During this period, he also produced industry research reports on artificial intelligence and its financial applications. The company ceased operations after returning capital to investors, and its intellectual property was acquired.
Alongside these roles, Jayant has been a guest speaker at London Business School since 2023, delivering lectures on digital investing and cryptocurrency. He was also recognized under the Tech Nation Exceptional Talent program from 2023 to 2026. In 2025, he co-founded Aivos Labs, where he continues to serve in a leadership role. The same year, he became Chief Strategy Officer at OpenGradient, a network focused on artificial intelligence infrastructure. [2] [4]
On the OpenGradient podcast, Matthew Wang and Jayant explored the innovations in AI and blockchain technologies, highlighting the design of the OpenGradient network, which used node specialization to balance scalability and decentralization. They emphasized the importance of privacy through hardware-based confidentiality in AI workflows, addressing concerns about data manipulation and the regulatory risks posed by centralized providers like OpenAI. Wang introduced TwinFun, a platform that enables users to create and share AI digital twin clones of themselves, which can evolve to perform complex tasks such as investment or automation, with features including verifiable interoperability and agent-to-agent interactions. They envisioned a future in which digital twins could autonomously handle tasks such as booking flights or negotiating prices, leveraging hyper-specialized agents to create a new economy driven by trustless interactions and dynamic pricing strategies. The speakers underscored that success depended on developing highly specialized AI agents capable of outperforming humans in specific domains, ultimately aiming to free humans from mundane work and enhance productivity through this rapidly advancing ecosystem. [5]
At BUIDL Europe in February 2026, Jayant moderated a fireside chat between co-founders Adam Balogh (OpenGradient) and Illia Polosukhin (NEAR), who discussed their visions of an "agentic internet," where users delegate tasks to autonomous digital agents rather than navigating the web themselves. Balogh described his transition into the AI agent space, highlighting his experience at Palantir, where he helped integrate AI into various products. Polosukhin emphasized the evolution from simple AI software to fully autonomous agents capable of pursuing goals independently, raising significant questions about governance, privacy, and verification. Both co-founders envisioned a future in which agents would not only manage mundane tasks but also create personalized experiences and assist users in achieving their goals, thereby transitioning towards a more mission-driven society. They expressed concerns about control, security, and privacy issues with these agents, advocating for user-owned data and verifiability to maintain trust in this evolving ecosystem. As they explored potential advancements in user interfaces and AI capabilities, they acknowledged the challenges posed by centralized models and the need for innovative, decentralized structures to enhance these technologies. [6]
In his talk at the Open-Source AI Summit in January 2026, Jayant discussed the importance of building transparency and verifiability into AI infrastructure to support an agentic world where AI agents perform tasks in the background. He shared his background in AI and crypto, emphasizing his focus on decentralization and secure data ownership. Jayant explained how OpenGradient developed a heterogeneous AI compute infrastructure that enabled verifiable on-chain inference, model verification, and secure data handling, with tools such as the Model Hub, which hosts numerous AI models. He illustrated practical applications such as AI for managing financial assets, reputation systems for decentralized compute networks, and autonomous robot operations, all of which emphasize the need for trust and security in critical domains like healthcare and finance. He also addressed concerns about data privacy, highlighting how their system ensures that private data remains confidential and that models remain tamper-proof by distributing operations across secure nodes, ultimately aiming to foster an ecosystem where more developers, models, and tools contribute to a trustworthy AI-powered future. [7]