OriginTrail's decentralized knowledge graph now enables Umanitek Guardian to provide verifiable provenance across AI systems, helping users protect their online identity from AI manipulation.
Key capabilities:
- Tracks content origins to counter deepfakes and identity abuse
- Provides verifiable, privacy-preserving infrastructure for AI systems
- Enables cross-border data coordination through AI agents like Luigi
The timing is critical. At Davos, global leaders emphasized the closing window to adapt to AI disruption, with Umanitek's Chris Rynning highlighting the need for AI safeguards as essential infrastructure.
At @wef Davos, the message from global leaders & AI experts is clear: the window to adapt to accelerating AI disruption is closing fast. We need to make AI safeguards essential infrastructure, emphasized @ChrisRynning – highlighting @umanitek Guardian, powered by @origin_trail.
AI makes impersonation, abuse, and identity misuse easier than ever. Who protects you in the age of AI? At @CV_Labs’ Web3 Hub in Davos, during @wef week, @umanitek Chairman @ChrisRynning took the stage to discuss a reality many already feel.
🤸 For European Gymnastics, we’re enabling secure cross-border data coordination with Luigi – an AI agent designed to operate on trusted, verifiable information across national boundaries.
🛡️Strengthening Internet safety with @umanitek Guardian, powered by @origin_trail – enabling verifiable content provenance & helping counter deepfakes, identity abuse, and manipulation in an AI-driven world.
When data origins are unclear, trust becomes a core challenge in AI today. Transparency and authenticity play a central role, as Charles Ivie, former Senior Graph Architect at @awscloud, explains. 🤝
At Davos, @umanitek made it clear: when trust fails, AI abuse becomes systemic. Trust belongs at the infrastructure layer - verifiable, privacy-preserving, interoperable by design, powered by @origin_trail.
🛡️@origin_trail gives @umanitek Guardian verifiable provenance across AI systems – so AI-manipulated outputs don’t define your identity online.
Umanitek detects and corrects false, harmful AI outputs across models and versions – before they define your reputation. See how you can protect your identity – book a demo now. ⤵️
As AI adoption accelerates, safeguards need to work at scale. @origin_trail DKG powers @umanitek Guardian to identify AI misuse across the internet. Protect your online identity - join the waitlist now. umanitek.ai/product/
Traces, knowledge, and reasoning paths form a reliable source of truth for AI agents. 🤝 Charles Ivie, former Senior Graph Architect at @awscloud, on why knowledge-backed traces are essential for trustworthy AI. 03:34 – Why data origin matters 07:17 – Interoperability and
From national platforms to European sports federations, trust is what enables AI to scale. Luigi, an AI agent powered by the @origin_trail DKG, enables secure cross-border data coordination for European Gymnastics on the road to LA 2028. 🤸
🧠 Knowledge as the New Asset Class

**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.
Data Verifiability Enables Shared Knowledge Through Discoverable Building Blocks
**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.
EU Project Launches Digital Building Logbook to Solve Fragmented Construction Data
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 Builds Sovereign Sports Data Foundation on OriginTrail for LA 2028 Olympics
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)
Why AI Agents Need Verifiability to Earn Our Trust

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.