OriginTrail

**DrevZiga presents at Consensus Hong Kong** on how decentralized knowledge graphs (DKG) are transforming real-world assets (RWAs). **Key points:** - Knowledge secured by DKG is emerging as a new asset class in the AI era - Presentation takes place at the EVOLVE Milegreen space - Builds on previous discussions about AI agents requiring memory and verifiable data infrastructure The talk explores how decentralized knowledge infrastructure is creating new opportunities for asset tokenization and AI applications.

**Discoverable data transforms isolated experiments into collaborative knowledge.** Noemi Friedman highlights how verifiable data infrastructure allows stakeholders to: - Identify data sources with confidence - Share information securely across teams - Convert individual experiments into collective insights OriginTrail's technology powers this data verifiability layer, building on earlier work establishing verifiable data as foundational infrastructure for financial and health markets. The focus remains on creating permissionless, decentralized systems that unlock practical use cases through trusted data sharing.

The EU-funded BUILDCHAIN project has introduced the **Digital Building Logbook**, addressing a critical challenge in Europe's construction and cultural heritage sectors: fragmented and unverifiable building data. **Key features of the solution:** - Powered by OriginTrail technology for data verification - Enables information retrieval from multiple repositories while maintaining data privacy - Ensures true data ownership for stakeholders - Reduces AI hallucinations through verifiable data foundations - Creates interoperable resources across building lifecycles **Real-world applications:** - Real-time monitoring of historical assets - AI agents built on verified data to protect cultural heritage - Transforms scattered building information into accessible, trustworthy resources The initiative tackles a problem affecting both modern construction projects and the preservation of Europe's architectural legacy, where reliable building data has historically been difficult to verify and access across different systems.

Azerbaijan's Ministry of Youth & Sports is constructing a national sports data infrastructure using OriginTrail's Decentralized Knowledge Graph technology as part of its **Invincible Azerbaijan at LA 2028** initiative. **Key Details:** - The government-backed program aims to create a trusted, sovereign data foundation for athlete development and sports programs - Data will remain connected and accessible across Olympic cycles, preventing information loss between competitions - Minister Farid Gayibov is overseeing the technology-driven approach to Olympic preparation - The initiative combines national sports infrastructure with AI capabilities The project represents Azerbaijan's strategy to leverage verifiable data systems for long-term athletic success, ensuring athlete performance metrics, training programs, and infrastructure improvements can be reliably tracked and shared over time. [Read more](https://x.com/origin_trail/status/2013256123273339038?s=20)

As AI agents gain the ability to act and transact on our behalf, the question of trust becomes critical. Drev Ziga explains that three key elements are essential for agentic systems to scale: - **Verifiability**: Ensuring actions can be confirmed and validated - **Provenance**: Tracking the origin and history of agent decisions - **Privacy**: Protecting user data while maintaining transparency Without these safeguards built in by design, autonomous AI systems operating 24/7 could pose significant risks. The conversation highlights how transparency and accountability must be foundational to agent-powered systems, not afterthoughts.

At the World Economic Forum in Davos, global leaders and AI experts delivered a stark warning: **the window to adapt to AI disruption is rapidly closing**. Chris Rynning emphasized the critical need to establish AI safeguards as essential infrastructure, highlighting Umanitek Guardian as a solution. The platform is powered by OriginTrail's Decentralized Knowledge Graph (DKG). **Key capabilities:** - Identifies AI misuse across the internet at scale - Protects online identity as AI adoption accelerates - Built on decentralized infrastructure for verifiable safeguards The message from Davos is clear: proactive measures are needed now, not later. [Join the waitlist]( https://umanitek.ai/product/) to protect your digital presence.

Charles Ivie, former Senior Graph Architect at AWS, discusses how knowledge-backed traces create trustworthy AI agents. **Key topics covered:** - Why data origin matters for AI reliability - Interoperability and trusted knowledge systems - Knowledge graphs as structured AI memory - How combining graphs improves trust The discussion addresses a core challenge: when AI agents act autonomously, the data shaping their decisions must be trusted and verifiable. Ivie explains how traces, knowledge, and reasoning paths form a reliable source of truth. Transparency and authenticity play a central role in making AI agents reliable at scale, particularly when data origins are unclear.

**DKGcon 2025 Day 2** featured hands-on workshops for building AI agents on the Decentralized Knowledge Graph. **Key Sessions:** - Zvonimir Šulac (OriginTrail Software Engineer) demonstrated building **DKG Agents** with reasoning, summarization, and data transformation capabilities - Infrastructure setup workshop for the new **DKG Edge Node** - the foundation for neuro-symbolic AI agents - Sessions focused on practical implementation rather than theory The conference continues OriginTrail's push into **trusted AI development** through decentralized knowledge graphs. Day 1 covered vision and roadmap, while Day 2 shifts to hands-on building. [Watch the live workshops](https://x.com/i/broadcasts/1djGXWdrZbOKZ?s=20) to learn agent development on the DKG platform.

**OriginTrail leadership presents major ecosystem update** Co-founders @DrevZiga, @TomazOT, and @BranaRakic unveiled OriginTrail's new strategic vision during a live presentation. **Key highlights:** - Introduction of the **Metcalfe Convergence Chapter** - Focus on exponential network effects through economic incentives - Integration of AI agents with trusted knowledge systems - Building shared content libraries to combat online harm in the AI era The presentation builds on OriginTrail's mission to power large-scale trade networks while expanding into AI-focused applications. **What's next:** The Metcalfe Convergence phase represents OriginTrail's evolution toward leveraging network effects for greater ecosystem impact.

**OriginTrail emphasizes privacy-preserving technology** in recent statements from co-founder and CTO Brana Rakic. Key features highlighted: - **Complete open-source architecture** for full transparency - **Data never leaves user devices** ensuring privacy protection - **In-depth visibility** into all system operations The technology's design prioritizes user control and data sovereignty. Users can verify exactly how their information is processed without compromising security. OriginTrail's approach addresses growing concerns about data privacy in decentralized systems. The open-source nature allows developers and users to audit the codebase independently. [Watch the full discussion](https://www.youtube.com/watch?v=aEiJ4r-nMi4)