Dimitri De Jonghe is a technologist working at the intersection of blockchain infrastructure, machine learning, and digital art. He is best known for early work on data-centric Web3 projects and for co-founding 204.ai, a creative studio and immersive lab focused on decentralized AI concepts and experimentation.
Overview
De Jonghe is commonly described as a co-founder and technical lead, with experience spanning research, product development, and applied engineering. His career has included roles in blockchain based data systems, IP and rights management for digital media, and projects exploring privacy, data sovereignty, and on-chain coordination for AI related workflows.
History and Background
De Jonghe holds a PhD in micro-electronics and machine learning from KU Leuven. His academic and engineering background has been tied to systems level thinking, with a focus on applying statistical and machine learning methods to complex technical domains. He later moved into Web3, contributing to projects that tried to make data exchange, provenance, and permissions more programmatic through decentralized systems.
Notable Contributions in Web3
De Jonghe has been credited as a co-founder and architect of BigchainDB and Ocean Protocol, projects associated with blockchain based data infrastructure and decentralized data market primitives. He also worked with ascribe, a blockchain project linked to digital media provenance and rights, and has been involved with Web3 entities including Temple Technology, Keyko, and Nevermined, described in CryptoSlate directory materials as advisory or co-founder roles.
- Ocean Protocol (2017 to 2020): Co-founder and Head of Research, focused on research and product direction for decentralized data concepts.
- BigchainDB (2016 to 2018): Co-founder, involved in business application direction for a blockchain database approach.
- ascribe (2014 to 2016): Contributor to early efforts around on-chain provenance for digital works.
Role at 204.ai
At 204.ai, De Jonghe is described as a co-founder and CTO. The studio positions itself as an R&D driven team exploring decentralized AI, with emphasis on data sovereignty, model and agent coordination, and privacy preserving approaches. Public descriptions also highlight an art and design orientation, including work on generative systems, immersive experiences, and new interfaces for human AI interaction.
In a CryptoSlate podcast interview, De Jonghe discussed decentralized AI as an extension of earlier Web3 data problems, including how data permissions, attribution, and incentive design can affect AI development and deployment.
Technology Themes and Focus Areas
- Data sovereignty: tooling and architectures that allow individuals or organizations to control access to datasets and derived outputs.
- Decentralized coordination: mechanisms for agents or services to collaborate without relying on a single operator.
- Privacy and rights: approaches that aim to preserve confidentiality and clarify ownership or usage permissions for data and creative outputs.
- AI plus art workflows: experimentation with generative systems and immersive interfaces, including work that blends technical R&D with creative production.
Relevance to the Crypto Ecosystem
De Jonghe’s work aligns with a broader industry effort to connect AI systems with verifiable data origins, programmable permissions, and transparent incentives. These topics are relevant to projects building data marketplaces, on-chain identity and credentials, and rights management for digital content. They also intersect with a growing interest in agent based systems that use blockchains for settlement, coordination, and auditability.
Risks and Considerations
Decentralized AI and data systems raise practical and policy questions. Privacy preserving architectures can be difficult to implement without sacrificing usability, and cross-jurisdiction data rules can affect how datasets are shared or monetized. Rights management in AI also remains contested, particularly where training data, licensing, and attribution are unclear. Projects operating in this area often need to balance open experimentation with robust security practices, clear governance, and compliance aware deployment strategies.
