OriginTrail

→ Global supply chains, on TRAC(k) → AI safety, on TRAC(k) → Medicines and science, on TRAC(k) → Rail and buildings, on TRAC(k) → Manufacturing, on TRAC(k) → Food, on TRAC(k) → Education, on TRAC(k) → International sports, on TRAC(k) Every one of these runs on data that passes between people and organisations who have never met: suppliers and buyers, labs and regulators, AI models and the people relying on their answers. When that data carries its owner, its origin and proof that it hasn't been changed, everything built on it stays on $TRAC(k). That is what the OriginTrail Decentralized Knowledge Graph (DKG) is for. Trust the source. 👉 origintrail.io/solutions

We need a collective immune system. A single compromised device let attackers drain ~$6.3B from @binance. One endpoint was enough. One prompt injection turned it into an attack vector. Isolated defenses clearly aren’t enough, Here's how to get protected for FREE👇 @umanitek’s Agent #Blackbox has every action is checked against verifiable threat intelligence on our Decentralized Knowledge Graph (DKG) before and agentic command is ran. One detection protects every agent. Shared, tamper-evident memory. Prompt injections, malicious packages, and dangerous commands get flagged or blocked on the spot. Trust the source.

A rail network is a multi-party system. Infrastructure managers, train operators, maintenance teams, and suppliers each hold part of the picture, and much of it changes in real time. Safety depends on that picture being connected, current, and verifiable at the moment a decision is made. Swiss Federal Railways (SBB) has been doing this in production since 2021, with @gs1 Switzerland and OriginTrail. Its EPCIS repository, built on the OriginTrail Decentralized Knowledge Graph (DKG), connects: → Train tracking across the EU, by querying a network of railway GS1 EPCIS repositories → Predictive maintenance of train wheels from IoT data → Welding and maintenance events across the SBB network, with input from more than 10 welding partners Teams query it in natural language and get verifiable AI answers. GS1's case study reports clear improvements in safety and sustainability. Read the case study 👉 gs1.org/insights-events/case…

🔴 Live today · 17:00 CET @umanitek’s Guardian is coming to @ChatGPT & @claudeai. Ask your AI assistant to find impersonators, build evidence packs, and request takedowns in one conversation. Every finding is anchored verifiably in the Decentralized Knowledge Graph.

Manufacturing, on TRAC(k). For the next decade. Data that can be verified is the cheapest form of AI risk management. It is also what the EU’s Digital Product Passports (DPP) will run on from 2027. In DMaaST, @JPB_SYSTEME and @KamstrupGroup are putting their factory data on the OriginTrail Decentralized Knowledge Graph to future-proof their smart manufacturing: verifiable records, traceable AI decisions, and DPP readiness built in. How it works: 👉 dmaast.eu/2026/10/20/the-mis…

The OriginTrail logo stands for trust. Organisations from very different worlds put it on the most valuable space they own: their products and their homepages. You'll find it at the centre of the QR code on millions of packs, where shoppers ask the brand questions directly through an AI agent. And on the homepage of European Gymnastics, the continental governing body for gymnastics in Europe, where "Powered by OriginTrail" sits under Luigi, its mascot turned AI agent. Both AI agents run on the OriginTrail Decentralized Knowledge Graph. Trust the source.