Oxford PharmaGenesis, serving 8 of the world's top 10 pharmaceutical companies and over 50 global healthcare organizations, is collaborating with OriginTrail to build trusted medical knowledge infrastructure for AI systems.
The partnership focuses on creating AI-ready medical knowledge with verifiable provenance. Dr. Kim Wager demonstrated how agentic medical AI can be grounded in data that can be independently verified, using OriginTrail's Decentralized Knowledge Graph (DKG).
Key features:
- Medical AI agents with transparent data sources
- Cryptographically verifiable knowledge assets
- Clear provenance trails for medical information
This collaboration addresses a critical need in healthcare AI: ensuring that autonomous systems operate on knowledge that can be traced, verified, and trusted. The approach aims to make medical AI more reliable by anchoring it in verifiable data rather than unverified sources.
With @ClawTrail, AI agents get their verifiable TRACk record. Agents can now prove what they've done, and how well. Powered by Decentralized Knowledge Graph (DKG). x.com/ClawTrail/stat…
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How can medical AI agents become more trustworthy? 🔍 Hear from Dr. Kim Wager of @OxPharmaGenesis as he showcases a live demo of agentic medical AI grounded in verifiable data provenance, powered by the @origin_trail Decentralized Knowledge Graph (DKG).
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How can we make medical AI agents more trustworthy? Dr. Kim Wager of @OxPharmaGenesis showed a medical AI agent that clearly displays where its data comes from and explains why it can be trusted - powered by @origin_trail. 🧠
2 BILLION Knowledge Assets 🎉 Published on the @origin_trail Decentralized Knowledge Graph. This isn’t just growth. It’s the rise of a verifiable memory layer for AI agents at a global scale. Every Knowledge Asset anchors facts, compliance records, certificates, supply chain
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Owning the context layer is one thing. Making it trustworthy for agents is another. That’s where @origin_trail Decentralized Knowledge Graph (DKG) comes in. 🕸️ With provenance, verifiability, and privacy built in, DKG enables a shared, verifiable memory layer for AI agents -
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AI is the frontend. Decentralized Knowledge Graph (DKG) is the backend. The Europe is on trac(k) 🇪🇺
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AI agents can’t operate on blind trust. They need verifiable identity, data provenance, and clear accountability. That’s the trust gap @wef is pointing to, and where @origin_trail delivers a trusted knowledge foundation agents can independently verify before they act. 🔍
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Start building AI agents on verifiable knowledge, designed for trust from day one. ⤵️ docs.origintrail.io
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Power your scientific AI with a verifiable knowledge infrastructure, powered by @origin_trail. docs.origintrail.io/?utm_source=x&…
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💊 The next generation of medicine will be built with AI. Dr. Kim Wager of @OxPharmaGenesis on why trusted, verifiable data is the foundation for safe and reliable medical AI agents.
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Discover how @origin_trail and @OxPharmaGenesis are advancing trustworthy AI and DeSci. ⤵️ x.com/origin_trail/s…
💊@OxPharmaGenesis, trusted by 8 of the world’s top 10 pharma leaders and 50+ global healthcare organizations, is joining forces with @origin_trail to advance trustworthy AI and pioneer DeSci! Together, we’re building collaborative, AI-ready clinical knowledge ecosystems to fuel
💊 Trusted medical AI starts with knowledge you can verify. In a live demo, Dr. Kim Wager of @OxPharmaGenesis showed how agentic medical AI can be grounded in verifiable provenance, powered by @origin_trail.
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GCC airspace broke down. Fake airline support accounts were in the replies within hours. We flagged 200+ impersonators across @emirates , @etihad , @qatarairways, @GulfAir - targeting passengers at their most vulnerable. AI made this effortless to run at scale - and it's only
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Build AI agents with verifiable memory. Free course at @origin_trail Academy ↓ academy.origintrail.io/course/trusted…
Discover how @OxPharmaGenesis, trusted by 8 of the world’s top 10 pharmaceutical companies and 50+ global healthcare organizations, and @origin_trail are building trusted medical knowledge for AI. 📚 origintrail.io/blog/oxford-ph…
AidTrust Tracks Donated Medicines Using Blockchain Technology
**AidTrust**, developed with BSI Group and powered by OriginTrail, provides a system for tracking donated medicines from source to patient. **Key features:** - Transparency across the distribution chain - Traceability of critical treatments - Trust verification for humanitarian supply chains The platform addresses a fundamental challenge in humanitarian aid: ensuring donated medicines reach their intended recipients rather than being diverted or lost in transit. Learn more: [BSI Group's AidTrust solution](https://www.bsigroup.com/en-IL/healthcare/donated-medicines-and-vaccines/)
OriginTrail Powers Supply Chain Security for 40% of US Imports
**SCAN Association's Trusted Factory** uses OriginTrail to verify supplier security audits before goods reach US borders. **Key Impact:** - Enables major importers to verify supplier security audits at the source - Reduces supply chain risk earlier in the process - Covers supply chains representing over 40% of US imports The system helps protect American consumers by ensuring security standards are met before products enter the country, rather than catching issues after arrival.
AI Agents Unite: DKG Powers Coordinated Intelligence Swarms

**AI agents are evolving from isolated tools to coordinated intelligence networks** on OriginTrail's Decentralized Knowledge Graph (DKG). **Key transformation:** - Isolation → coordinated swarms - Duplicated work → compounding knowledge - Probabilistic outputs → verifiable decisions Agents like OpenClaw, NemoClaw, and Hermes now operate as nodes in a shared memory system, publishing and verifying each other's work in real time. Every finding becomes a cryptographically anchored Knowledge Asset—verifiable, permanent, and queryable across the network. **Performance gains with DKG v9:** - Up to 60% faster - Up to 40% cheaper than traditional markdown handoffs The focus shifts to V10 mainnet deployment, unlocking the infrastructure for fully traceable, lightning-efficient agent coordination. The bottleneck is no longer capability—it's shared, verifiable memory.
🕸️ AI Agents Need Shared, Verifiable Memory to Scale Beyond Silos
**The Challenge of AI Memory Silos** Most AI memory currently exists in isolated systems, creating a fundamental scaling problem for multi-agent systems. **Why Verifiable Memory Matters** - AI agents cannot scale effectively on isolated memory - Multi-agent systems require **shared, verifiable memory** that works across different tools, teams, and workflows - Before agents take action, the knowledge they rely on must be **traceable and checkable** **The Trust Factor** Scaling AI isn't just about computational power—it's about scaling trust. For AI agents to collaborate effectively, they need memory with clear provenance that can be verified across systems. Learn more about building verifiable memory systems for AI: [Brana Rakic's thread](https://x.com/BranaRakic/status/2032877330209595723?s=20)