In a world increasingly driven by data and shaped by Artificial Intelligence (AI), ensuring the trustworthiness, transparency, and provenance of information has become a critical challenge. As AI systems grow more powerful and integrated into decision-making processes, the risks associated with misinformation, opaque algorithms, and centralized control rise dramatically. Establishing systems that can verify data authenticity, preserve ownership rights, and enable open participation is essential for a fair and secure digital future. One project addressing these challenges by merging Web3 infrastructure with AI-ready frameworks is the decentralized knowledge graph protocol known as OriginTrail.

What is OriginTrail (TRAC)?

Between 2013 and 2016, the groundwork for OriginTrail was laid through supply chain pilots across Europe. These early prototypes focused on organic beef, dairy, poultry, and vegetables, integrating with enterprise resource planning (ERP) systems like Microsoft Navision and SAP. By 2017, OriginTrail began linking users to Ethereum and established a project office in Shanghai. In early 2018, the team led by Žiga Drev, Tomaž Levak, and Branimir Rakić launched an initial coin offering, raising $22.5 million in under 20 minutes. This rapid success led to the development of the OriginTrail Decentralized Knowledge Graph (DKG), an infrastructure adopted by enterprises such as BSI, SBB, and WFH. Between 2018 and 2022, OriginTrail launched its permissionless mainnet, introduced zero-knowledge layers, and refined its incentive models and bidding mechanisms through multiple versioned releases. Trace Labs, the core development company based in Hong Kong, won the Walmart Food Safety Innovation Spark Award during this period. In 2022, the second whitepaper was released, further detailing the tokenization of real-world assets and the role of the DKG. In late 2023, the Turing phase introduced DKG V6 and the AI-aligned ChatDKG, addressing the trust gap in generative AI. By 2024, OriginTrail launched its NeuroWeb blockchain to support the expansion of the knowledge graph across EVM chains. As of April 2025, the Metcalfe phase is ongoing, centered around DKG V8 and decentralized AI verifiability. Inspired by Bob Metcalfe, this phase emphasizes Retrieval-Augmented Generation (dRAG) and knowledge inferencing. With over a decade of development, OriginTrail continues to push boundaries in trusted data infrastructure, supporting sectors such as supply chains, healthcare, and AI.

OriginTrail was created to build a Verifiable Internet for AI, grounded in neutrality, inclusiveness, and usability, enabling trusted data infrastructure for decentralized AI and Web3 systems.

How Does OriginTrail Work? Decentralized Knowledge Graph and NeuroWeb

OriginTrail operates through a sophisticated data infrastructure known as the Decentralized Knowledge Graph (DKG), a system purpose-built to bring verifiability, ownership, and accessibility to digital knowledge in a decentralized environment. In a digital age saturated with misinformation, the ability to verify and own knowledge is increasingly vital, especially for artificial intelligence (AI) systems that rely on accurate, real-time data inputs. The DKG is designed to address these challenges by turning data into AI-ready, verifiable Knowledge Assets accessible via a decentralized network of nodes.

Source: origintrail whitepaper

The OriginTrail DKG is an open-source network structured into three interconnected layers that form a neuro-symbolic AI stack. The trust layer ensures data integrity using blockchain technology. The knowledge base layer applies symbolic AI to structure and reason about knowledge effectively. Lastly, the verifiable AI layer employs neural AI models for automation and adaptability. Together, they provide a robust system for organizing, retrieving, and validating information.

One of the most advanced features of the OriginTrail DKG is its implementation of Decentralized Retrieval-Augmented Generation (dRAG). Based on the concept of Retrieval-Augmented Generation (RAG), dRAG enhances generative AI systems by integrating symbolic AI through a decentralized knowledge graph. This enables systems to fetch relevant, verified knowledge before generating responses, thus improving the accuracy and relevance of AI outputs. dRAG is especially valuable because it merges the generalization strengths of neural networks with the precision and contextual reasoning of symbolic AI.

Source: origintrail.io

Within the DKG, Knowledge Assets serve as the core unit of information. These are multi-format, ownable containers of knowledge, uniquely identifiable by Uniform Asset Locators (UALs). Ownership is managed through NFTs, allowing for secure control and monetization of data. Discoverability is inherent in their structure, utilizing linked data principles and enabling connections across the internet. Verifiability is ensured through Merkle-tree-based cryptographic proofs recorded on-chain, making each asset auditable and resistant to tampering.

AI systems and agents can access these Knowledge Assets with precision, using symbolic and neural query methods. Whether powering chatbots, autonomous agents, or large language models, the DKG provides a transparent and traceable foundation for AI. Each asset can be queried, verified, and integrated, forming a network of interoperable and reliable data sources that support trusted AI applications.

Ultimately, the OriginTrail DKG redefines data utility in the Web3 and AI age by transforming knowledge into a decentralized, ownable, and verifiable asset class. It forms the backbone of a Verifiable Internet for AI, ensuring that both humans and machines can access accurate and trusted information in real-time, with guarantees of provenance, ownership, and integrity.

NeuroWeb

At the heart of OriginTrail’s infrastructure evolution lies the NeuroWeb, a purpose-built Layer 1 blockchain designed to enhance the decentralized knowledge economy through tight integration with knowledge graphs and artificial intelligence. NeuroWeb operates as a multichain innovation hub, aligned with the principles of neutrality, inclusiveness, and usability. Built using the Substrate framework and secured by Polkadot, it supports EVM compatibility, making it interoperable with Ethereum and other Ethereum Virtual Machine (EVM) networks. Through these integrations, NeuroWeb facilitates a seamless expansion of the OriginTrail Decentralized Knowledge Graph (DKG) across ecosystems.

Source: origintrail.io

The NeuroWeb is governed by the OriginTrail community and fueled by the NEURO token. This native utility token underpins the platform’s core economic and governance functions, including incentivization of network participants, staking, and knowledge mining. The DKG V6 was deployed on NeuroWeb, marking a crucial step toward building verifiable AI by enabling scalable, decentralized data infrastructures across blockchain ecosystems. Through the DKG V6, interconnected Knowledge Assets can be developed and maintained across multiple networks, including Polkadot parachains and EVM-compatible chains.

One of the defining innovations of NeuroWeb is its support for Decentralized Retrieval-Augmented Generation (dRAG), a framework that enhances generative AI models with trusted external knowledge. As the amount of available knowledge in the DKG expands, dRAG becomes more effective. To drive this growth, NeuroWeb enables knowledge mining—an incentivized mechanism allowing individuals or organizations to create, validate, and share Knowledge Assets within specific “paranets.”

Paranets are thematic or domain-specific segments of the DKG that can be autonomously created and managed. Operators of these paranets can propose reward structures through decentralized governance, defining how NEURO token emissions are distributed. Rewards may incentivize tasks such as ontology validation, AI service provision, or data curation. These dynamic governance mechanisms ensure that NeuroWeb remains adaptable, fostering both broad and niche data spaces according to evolving community needs.

Crucially, the NeuroWeb’s incentive system supports both manual and autonomous knowledge mining. In the early stages, participants gather and structure knowledge manually. As data within a paranet matures—annotated and compliant with ontological standards—AI systems can employ deductive and inductive reasoning to generate new knowledge autonomously. Deductive reasoning follows logical rules to derive insights from existing knowledge, while inductive reasoning, powered by tools such as Graph Neural Networks (GNNs), identifies patterns to make probabilistic inferences and predictions.

The convergence of the DKG, NeuroWeb, and AI through the dRAG framework introduces a new era of autonomous knowledge creation. Knowledge Assets become dynamically interconnected, continuously verified through cryptographic proofs, and increasingly enriched via AI inference. This symbiosis enhances the integrity, relevance, and utility of AI systems, aligning them with Web3 values of transparency, user control, and decentralization.

OriginTrail Use Cases

OriginTrail leverages its Decentralized Knowledge Graph (DKG) to address real-world challenges across multiple sectors. By enabling verifiable, trusted data exchange, OriginTrail empowers organizations to build safer, more efficient, and transparent systems in critical industries.

1. Safer Internet in the Age of AI: OriginTrail is addressing the growing concerns around deepfakes, intellectual property violations, and illicit content such as CSAM by introducing a trusted data infrastructure. As AI evolves, so do its risks—especially with the mass production of misinformation and harmful media. OriginTrail supports a verifiable internet by enabling transparency, ownership, and trust. By fostering a decentralized, censorship-resistant, and interoperable ecosystem for digital content, it empowers ethical innovation and protects both individuals and institutions in an increasingly AI-driven online landscape.
2. Decentralized Science & Research Integrity: OriginTrail is pioneering decentralized science (DeSci) to tackle issues like misinformation, publication bias, and predatory publishing. By transforming data into verifiable, interconnected Knowledge Assets, researchers can access accurate, traceable information with clear provenance. Projects like SciGraph use the DKG to connect data and enable AI-driven hypothesis generation, supporting a more transparent and collaborative research environment. This allows the scientific community to build trust, improve reproducibility, and unlock faster, more credible breakthroughs across fields such as climate science and healthcare.
3. Transparent Supply Chains: Global supply chains are often opaque, raising concerns about sustainability, human rights, and product safety. OriginTrail’s DKG enables secure, privacy-preserving sharing of verified data across networks, promoting traceability and collaboration. It is already in use by major initiatives, such as the Supplier Compliance Audit Network (SCAN), with members including Walmart and Costco. Through Knowledge Assets, OriginTrail supports ESG standards, reduces audit duplication, and ensures regulatory compliance, thereby fostering ethical, sustainable, and efficient trade ecosystems.
4. Smart Infrastructure & Construction: In construction, OriginTrail addresses the lack of trustworthy building data, which hampers sustainability and safety. Its decentralized graph system ensures verifiable records for projects, materials, and compliance. Used in the BuildChain project, OriginTrail technology integrates with the EU’s Digital Building Logbook, enabling all stakeholders—architects, contractors, owners—to access real-time, tamper-proof building data. This improves efficiency, enhances disaster preparedness, and lays the groundwork for smarter, greener, and more accountable infrastructure.

OriginTrail Main Features

Autonomous Paranets

Paranets are independently operated subnetworks within the Decentralized Knowledge Graph (DKG), created and managed by individuals, organizations, or DAOs. Each paranet includes its own curated set of Knowledge Assets, AI services, and reward structures for incentivizing contributors. These assets may focus on specific topics, like LLM training data, social media, Industry 4.0, or public company reports. Paranets utilize dRAG (Decentralized Retrieval-Augmented Generation) to aggregate accurate information from public and private sources across the DKG. Their characteristics—including ontology rules, data formats, and growth incentives—are defined by paranet operators. Each paranet runs on a supported blockchain, allowing global interoperability within the DKG. The modular and permissionless nature of paranets empowers anyone to contribute trusted knowledge, enabling AI systems to scale in intelligence and specificity. This structure fuels a decentralized, crowdsourced model for data generation and AI optimization across industries and domains.

Source: origintrail whitepaper

Neuro-Symbolic Harmony

OriginTrail fosters a unique synergy between symbolic and neural AI systems, combining fact-based knowledge graphs with the generative capabilities of large language models. This hybrid model, known as neuro-symbolic AI, enables systems to reason and create, utilizing structured, verifiable data to support imaginative and creative output. The symbolic layer (powered by the DKG) ensures data integrity, traceability, and ownership, providing a robust factual foundation. Meanwhile, the neural layer (such as LLMs) adds dynamic, multimodal creativity across text, image, and audio. This architecture enables users to select their preferred AI models and integrate them with reliable data sources. Whether designing AI assistants or building advanced machine-learning pipelines, developers benefit from OriginTrail’s balance between structure and innovation. The system offers composability and control without compromising the adaptive power of neural networks, enabling scalable, transparent AI that’s not only intelligent, but also accountable and inclusive.

Source: origintrail.io

ChatDKG

ChatDKG is a builder-friendly platform that transforms your data into usable, verifiable Knowledge Assets, enabling the development of reliable, AI-driven applications. These assets are created on the OriginTrail Decentralized Knowledge Graph (DKG), ensuring data provenance and giving creators full control over visibility and usage. Once the assets are live, developers can deploy AI agents with predictable behavior, enhanced by integrations with top AI models, including OpenAI, Microsoft Copilot, Llama Index, and Hugging Face. ChatDKG also allows users to launch new paranets, establishing niche knowledge hubs that can receive network incentives. To foster ecosystem growth, ChatDKG includes mechanisms for requesting incentivization for each new, relevant Knowledge Asset added. This not only increases asset quality and quantity, but also sustains an economy of trusted data and reliable agents. Whether you’re building a search engine, analytics tool, or AI chatbot, ChatDKG streamlines the process—offering a bridge between your data and intelligent, autonomous systems.

Source: chatdkg.ai

AI Agents in Action

OriginTrail’s ChatDKG enables real-world AI applications across various industries through smart agents operating on verified knowledge. One example is PolkaBot.ai, an AI-powered educational tool tailored to the Polkadot ecosystem. It leverages community-curated Knowledge Assets to deliver trusted insights and learning resources. In the food sector, Perutnina Ptuj uses decentralized AI to enhance consumer trust by verifying product authenticity at every touchpoint. Similarly, ChatDKG powers smart agents in Europe’s construction sector, assisting builders with trusted data and compliance. In aerospace, OriginTrail is behind an EU-funded initiative advancing the Digital Product Passport, helping industries improve traceability and responsiveness to unforeseen events. These use cases demonstrate the diverse potential of ChatDKG, ranging from enhancing user engagement to ensuring data safety and facilitating scalable regulatory solutions. Each AI agent is tied to verifiable data on the DKG, ensuring reliability, auditability, and autonomy, ultimately redefining the future of human-machine collaboration in critical industries.

Source: chatdkg.ai

Core Node

The Core Node is the backbone of the DKG, securing the network and earning TRAC rewards from global data activity. By staking a minimum of 50,000 TRAC, operators help maintain the network’s resilience, security, and trustworthiness. Core Nodes host public Knowledge Assets and participate in distributing rewards based on overall DKG usage. They can boost earnings further through delegated staking, where other TRAC holders contribute to the node’s stake. Notably, the Core Node includes all Edge Node features, providing the same tools for building verifiable AI while adding critical infrastructure support for the growing knowledge economy.

Source: origintrail.io

Edge Node

The Edge Node is a user-friendly gateway to the OriginTrail Decentralized Knowledge Graph (DKG), enabling developers to build verifiable, trusted AI applications. Through a streamlined interface or API, users can upload diverse data formats—like PDFs, Word documents, or web content—and convert them into semantically rich Knowledge Assets. Edge Nodes give full control over data privacy, allowing selective sharing on the DKG. With built-in support for decentralized Retrieval Augmented Generation (dRAG), users can interact with knowledge directly or via an AI assistant. Flexible AI integration options enable local model deployment or external service connections, striking a balance between privacy and scalability.

Source: origintrail.io

What is the TRAC Coin?

TRAC is the native token powering the OriginTrail Decentralized Knowledge Graph and ecosystem. Its total supply counts 500 million units, most of which (499.4 million) are already in circulation (April 2025).

As OriginTrail expands to address the challenges of misinformation, decentralized AI, and Web3 infrastructure, TRAC plays a central role in incentivizing, securing, and enabling operations across the network. Each time a Knowledge Asset is created on the DKG, it consumes network resources. TRAC is used to pay for this service, acting as the access fee for publishing and updating assets within the system. Although TRAC is not used as gas directly on all chains, since that depends on the blockchain (e.g., ETH on Ethereum or NEURO on NeuroWeb), it is still a core payment and incentive asset across the OriginTrail infrastructure.

Nodes within the DKG compete to provide publishing services and earn TRAC fees. Their success depends on service quality, the amount of TRAC staked, and paranet-related configurations. Because TRAC staking determines which nodes can participate and earn, TRAC delegation has emerged as an essential function of the network. Any TRAC holder can delegate tokens to a Core Node and earn proportional rewards. This delegated staking system strengthens the security and resilience of the DKG by ensuring nodes are properly incentivized and penalized if they misbehave. TRAC staking effectively ensures network reliability and economic alignment between participants.

Launched as an ERC-20 token on Ethereum in 2018, TRAC’s utility has since expanded significantly. In addition to being used for node staking and Knowledge Asset operations, it serves as a medium of value transfer within the OriginTrail ecosystem. The token distribution is structured as follows: 50% was allocated to the presale and crowdsale, 20% to future development, 18% to founders and Pre-ICO contributors, 5% to the team and advisors, 5% to the liquidity pool, and 2% to bounties. This allocation supports long-term growth, network incentives, and decentralized participation in the ecosystem.

Source: medium.com/origintrail

Is TRAC a Good Investment?

TRAC benefits from strong utility within the OriginTrail ecosystem, serving as the economic engine for the Decentralized Knowledge Graph (DKG), which addresses pressing issues like AI transparency and misinformation. Its delegated staking model and integration with real-world enterprises add credibility. However, the project faces the challenge of adoption beyond niche sectors. Its technical complexity and reliance on long-term Web3 and AI convergence may limit near-term traction. Market volatility and limited mainstream awareness also pose risks for TRAC’s broader success and potential value appreciation.

How to Own TRAC?

To own TRAC, you can use the services of a centralized crypto exchange. Start by creating a Gate.io account, and get it verified and funded. Then you are ready to go through the steps to buy TRAC.

News on OriginTrail

As reported on the official OriginTrail blog, the ecosystem unveiled its 2025 roadmap, spotlighting the launch of Impact Base: Gaia and the milestone deployment of DKG V8. This update accelerates collective neuro-symbolic AI with scalable tools like Edge Nodes, private knowledge repositories, and autonomous inferencing. The roadmap also introduces the 60M TRAC Collective Programmatic Treasury (CPT) to reward ecosystem contributors. With breakthroughs in privacy, AI integration, and verifiable knowledge mining, OriginTrail continues to evolve as the foundational layer for a trusted, decentralized AI-powered internet.

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