OriginTrail

OriginTrail (TRAC) — a reference card for a crypto project: what the product does and how verifiable the project’s key claims are; also — alignment with the Decentralized AI thesis (DecAI Fit).

OriginTrail — a project around a Decentralized Knowledge Graph (DKG) and the idea of a “Verifiable Internet for AI” (dRAG): storage/discovery/verification of Knowledge Assets used by AI systems. The TRAC token is described as a utility token for the operation and incentives of the DKG (publishing/staking/delegation, etc.).

Disclaimer

Important: this page is a reference overview of the project. Within DecAIHub, we separately record a verification based on open sources within the AI thesis (what is real AI/onchain/why a token, and which sources this is based on).
This is not financial advice and not a recommendation to buy/sell/hold any asset. We do not assess price, returns, or entry/exit timing.
Conclusions are based on publicly available materials found as of the verification date. The absence of confirmation does not imply the absence of the technology.

TL;DR (for readers who are not into AI)

What it is: a DKG (Decentralized Knowledge Graph) infrastructure for publishing/searching/verifying “Knowledge Assets”, intended to improve the reliability of AI (dRAG / verifiable inputs).
Who it’s for: developers of AI systems/agents (RAG/dRAG), publishers of knowledge/data, node runners and stake delegators.
Why onchain/token: the blockchain is used for ownership/verifiable proofs of the state of Knowledge Assets; TRAC is the utility token for compensating DKG services and for node staking/delegation/slashing.

How it works (very briefly)

The user does: publishes a Knowledge Asset to the DKG or uses already published ones for an AI process (dRAG/RAG).
The system does: stores/replicates the data on DKG nodes and records onchain proofs of state/verifiability (Merkle proofs/digests).
The user gets: discoverable and verifiable knowledge that can be mixed into AI answers/agents to reduce the risk of hallucinations/forgeries.
Where the blockchain is: ownership (via NFTs) and state proofs of Knowledge Assets; multichain integrations are mentioned in the materials.
Token role: TRAC is used for compensating DKG services (publishing fees) and for staking/delegation/slashing as the node security mechanic.

Quick links: AI thesis fit

Project passport

Field	Value
Project name	OriginTrail
Also known as (aliases)	TRAC, OriginTrail DKG
Logo (logo)	../assets/15_origintrail_logo.svg
Token symbol (ticker)	TRAC
Category	AI/Other \| Infra
Primary chain (chain)	Ethereum
Type	EVM
Network status	mainnet
Consensus (consensus)	PoS (Ethereum)
Launch date (launch_date)	2018
Project status (status)	active
Token (standard)	ERC-20
Token contract	0xaa7a9ca87d3694b5755f213b5d04094b8d0f0a6f
Token model (token_type)	utility (publishing + staking)
Max supply	500000000 (TRAC)
Issuance	fixed (non‑inflationary)
Tokenomics (tokenomics, brief)	TRAC for DKG publishing fees + node collateral/delegation/slashing; multichain
Governance	onchain governance (NeuroWeb/NEURO), details —
Admins/keys	—
Audit	yes
Bug bounty	yes
Team (team)	Trace Labs / OriginTrail core developers
Funding (investors/funding)	—
AI component (ai_component)	DKG + dRAG for verifiable AI
Use‑case (use_case)	verifiable knowledge assets for AI
DecAI Fit — AI thesis fit	3/6 — medium alignment with the Decentralized AI thesis
DecAI Fit component summary	1 / 3 / 2 / 3
Last verified	2026-02-10

Links (links_*)

Type	Link
Website	https://origintrail.io/
Docs	https://docs.origintrail.io/
GitHub	https://github.com/OriginTrail/dkg-engine
Releases / Changelog	https://github.com/OriginTrail/dkg-engine/releases
Whitepaper	https://origintrail.io/documents/Verifiable_Internet_for_Artificial_Intelligence_whitepaper_v3_pre_publication.pdf
Roadmap	https://origintrail.io/ecosystem/roadmap
Security advisories	https://github.com/OriginTrail/dkg-engine/security
Explorer	https://etherscan.io/token/0xaa7a9ca87d3694b5755f213b5d04094b8d0f0a6f
X	https://twitter.com/origin_trail
Discord	https://discord.com/invite/xCaY7hvNwD
Telegram	https://t.me/origintrail
Medium	https://medium.com/origintrail
Audit report(s)	https://github.com/OriginTrail/smart-contract-audit-documents
Bug bounty	https://docs.origintrail.io/contribute-to-the-dkg/bounties-and-rewards/general-bug-bounty
CoinGecko (profile, reference)	https://www.coingecko.com/en/coins/origintrail
CoinMarketCap (profile, reference)	https://coinmarketcap.com/currencies/origintrail/

General project overview

OriginTrail describes the “Verifiable Internet for AI” as an approach in which AI systems use verifiable sources of knowledge to reduce the risks of hallucinations, provenance problems and tampering. The central component is the OriginTrail Decentralized Knowledge Graph (DKG), a permissionless network of knowledge graph nodes integrated with several blockchains. The whitepaper describes Knowledge Assets as containers of knowledge for which proofs of state (digests/Merkle proofs) are recorded onchain, and ownership is implemented via NFTs.

Features/modules

Decentralized Knowledge Graph (DKG): a network of nodes providing discoverability/availability of knowledge.
Knowledge Assets: ownable containers of knowledge (including triples, embeddings, images), with verifiability via onchain proofs and NFT ownership.
dRAG (Decentralized RAG) framework: the concept of integrating DKG sources into AI answer generation.
Paranets: autonomous “sub-networks” (topic/vertical) with knowledge assets and services, including incentivization.

Typical scenarios

Scenario 1: a publisher publishes a Knowledge Asset → pays TRAC for the DKG service → gets a discoverable/verifiable asset.
Scenario 2: an AI developer uses dRAG → retrieves facts from Knowledge Assets → gets answers with provenance and verifiability.
Scenario 3: a node runner runs a node and attracts delegated TRAC → receives fees/rewards for correct operation (and bears the risk of slashing for malicious behavior).

Getting started (wallet/network)

What you need: choose a network/tools in the OriginTrail ecosystem and have TRAC for publishing/staking scenarios.
Network/chain: TRAC started as an ERC‑20 on Ethereum; the token page describes multichain.
Fees: publishing requires TRAC for the DKG service and the gas token of the selected network (the whitepaper lists examples).

Architecture/tech (non‑AI)

Components: DKG nodes, Knowledge Assets, onchain proofs/ownership, integrations with several blockchains, tooling/engine (GitHub).
Participant roles: publishers, consumers/AI apps, node runners, delegated stakers/delegators, paranet operators.
Where logic runs: data storage/replication — on DKG nodes; ownership/proofs and part of the operations — onchain.
Dependencies: host blockchains (Ethereum and others), wallets/tools, GitHub repositories.

Token/economics (expanded, no forecasts)

Token utility: TRAC is used for compensating DKG services when publishing Knowledge Assets and for node stake/delegation (whitepaper + TRAC token page).
Protocol necessity drivers: publishers pay TRAC for DKG services; nodes compete and depend on stake; delegators increase a node’s stake.
Who pays fees: the publisher pays TRAC + the network’s gas token (e.g., ETH/DAI/NEURO per the whitepaper).
Where fees go: publishing fees go to DKG nodes (whitepaper).
Issuance/burn: TRAC is described as non‑inflationary with a fixed supply of 500M.
Security/incentive mechanisms: collateral/staking and slashing for nodes; delegated staking (whitepaper + token page).
Distribution: the token page says “all tokens are in circulation”; additional distributions/vesting — not recorded as a passport fact.
Treasury: —.

Governance

Who makes decisions: in the whitepaper, governance over incentivization is described via NeuroWeb/NEURO community voting.
How protocol parameters change: proposals/voting in the context of incentives and related mechanisms.
Where decisions are discussed: Discord/Docs/GitHub.
Keys/multisig: —.

Security and incidents

Audits: yes (see links_*).
Bug bounty: yes (see links_*).
Incidents: —.
Threat model: risks to the correctness of proofs/ownership, node and slashing risks, risks of multichain components.

Project status and timeline

Current status: active.
Key releases/milestones: TRAC launched in 2018 (token page); the “Verifiable Internet for AI” whitepaper — pre‑publication v3.
Roadmap: see links_*.

Ecosystem/integrations

Integrations: multichain TRAC (Ethereum/Polkadot parachain/Gnosis/Polygon per the token page); the GitHub engine and tooling; AI/RAG tools as consumers of the DKG.
Partners: —.
Where it’s actually used: publishing/hosting Knowledge Assets and their consumption in dRAG scenarios.

AI component of the project

What is real AI here? The project positions itself as infrastructure for improving the reliability of AI (dRAG, verifiable inputs). This is AI‑intent/AI‑use‑case, not confirmation of its own AI model with quality metrics.
What is truly onchain? Ownership of Knowledge Assets via NFTs and state proofs (Merkle‑proof digests) + onchain publish/update operations.
Why is a token needed? TRAC is used to pay for DKG services and for node stake/delegation/slashing.
Red flags (based on the information found): AI‑washing — medium risk (AI as “trusted AI infra”, no model metrics); onchain‑washing — low risk (onchain proofs/ownership are core); token‑washing — low risk (the TRAC utility is described in detail by Tier‑1).

DecAI Fit component summary

DecAI Fit: 3/6 — medium alignment with the Decentralized AI thesis

Component	Level	Score
AI reality	low	1
Onchain necessity	high	3
Token necessity	medium	2
Evidence	Tier‑1 present	3

Details

AI reality

AI_0 — AI intent (Tier‑1 roadmap) (1/0)

AI_0 (decision): 1
Claim (one line): the whitepaper formulates the goal of a “Verifiable Internet for Artificial Intelligence” and dRAG as a framework for AI systems.
Evidence: Tier‑1 — https://origintrail.io/documents/Verifiable_Internet_for_Artificial_Intelligence_whitepaper_v3_pre_publication.pdf
Why sufficient / why not (one line): this is Tier‑1 AI positioning/intent.
Conflict note (if any): —

AI_1 — what the AI does (1/0)

AI_1 (decision): 0
Claim (one line): the project does not prove the existence of its own AI model/inference; it provides a verifiable knowledge layer for AI.
Evidence: Tier‑1 — —
Why sufficient / why not (one line): Tier‑1 describes the DKG and dRAG infrastructure, not a specific AI model.
Conflict note (if any): —

AI_2 — demos/examples (1/0)

AI_2 (decision): 0
Claim (one line): no Tier‑1 demo of an “AI model” as a component of the protocol was found.
Evidence: Tier‑1 — —
Why sufficient / why not (one line): here AI is a consumer of the verifiable knowledge layer.
Conflict note (if any): —

AI_3 — metrics/quality (1/0)

AI_3 (decision): 0
Metrics: —
Context (version/date/how measured): —
Evidence: Tier‑1 — —
Why sufficient / why not (one line): there are no AI model quality metrics.
Conflict note (if any): —

AI_4 — tech description/architecture/versions (1/0)

AI_4 (decision): 0
Claim (one line): a technical description of an AI model/versions is not applicable; Tier‑1 describes dRAG/DKG as infrastructure.
Evidence: Tier‑1 — —
Why sufficient / why not (one line): this is AI infra, without a description of a specific model.
Conflict note (if any): —

Onchain necessity

OC_1 — contracts/addresses/chain (1/0)

OC_1 (decision): 1
Chain: Ethereum mainnet (TRAC ERC‑20; also multichain).
Addresses/identifiers: TRAC ERC‑20: 0xaa7a9ca87d3694b5755f213b5d04094b8d0f0a6f
Evidence: Tier‑1 — https://origintrail.io/get-started/trac-token ; https://etherscan.io/token/0xaa7a9ca87d3694b5755f213b5d04094b8d0f0a6f
Why sufficient / why not (one line): the token page + the explorer confirm the token address and the network.
Conflict note (if any): —

OC_2 — onchain beyond just a token (1/0)

OC_2 (decision): 1
What useful logic is onchain: ownership of Knowledge Assets via NFTs and the storage of Merkle proofs/digests on the blockchain (verifiability).
Evidence: Tier‑1 — https://origintrail.io/documents/Verifiable_Internet_for_Artificial_Intelligence_whitepaper_v3_pre_publication.pdf
Why sufficient / why not (one line): the whitepaper describes NFT ownership and onchain proofs as core properties of Knowledge Assets.
Conflict note (if any): —

OC_3 — onchain is critical (1/0)

OC_3 (decision): 1
“Replace the blockchain” test: without onchain, the trustless verifiability/ownership of Knowledge Assets breaks down (and this is declared as the foundation of the “Verifiable Internet for AI”).
Evidence: Tier‑1 — https://origintrail.io/documents/Verifiable_Internet_for_Artificial_Intelligence_whitepaper_v3_pre_publication.pdf
Why sufficient / why not (one line): onchain proofs/ownership are the key value.
Conflict note (if any): —

Token necessity

TK_0 — no token (1/0)

TK_0 (decision): 0
Claim (one line): the project uses the TRAC utility token.
Evidence: Tier‑1 — https://origintrail.io/get-started/trac-token
Why sufficient / why not (one line): the token page describes the TRAC utility.
Conflict note (if any): —

TK_1..TK_4 (1/0)

TK_1 — payment for the service (1/0)

TK_1 (decision): 1
Claim (one line): when publishing Knowledge Assets, TRAC is used to compensate DKG services (publishing fees).
Evidence: Tier‑1 — https://origintrail.io/documents/Verifiable_Internet_for_Artificial_Intelligence_whitepaper_v3_pre_publication.pdf ; https://origintrail.io/get-started/trac-token
Why sufficient / why not (one line): the whitepaper and the token page describe paying for DKG services in TRAC.
Conflict note (if any): —

TK_2 — incentives/collateral/penalties (1/0)

TK_2 (decision): 1
Claim (one line): TRAC is used as collateral/stake for DKG nodes, with the possibility of delegation and slashing for malicious behavior.
Evidence: Tier‑1 — https://origintrail.io/documents/Verifiable_Internet_for_Artificial_Intelligence_whitepaper_v3_pre_publication.pdf ; https://origintrail.io/get-started/trac-token
Why sufficient / why not (one line): the whitepaper describes delegated staking and slashing; the token page describes collateral/delegation.
Conflict note (if any): —

TK_3 — governance (1/0)

TK_3 (decision): 0
Claim (one line): governance voting on incentives is described via the NEURO token community; TRAC‑based governance is not recorded as a fact.
Evidence: Tier‑1 — —
Why sufficient / why not (one line): in the whitepaper, governance is linked to NEURO (NeuroWeb), and TRAC — to utility/staking.
Conflict note (if any): —

TK_4 — token is replaceable (1/0)

TK_4 (decision): 0
Claim (one line): the replaceability of TRAC with an alternative asset is not established per Tier‑1.
Evidence: Tier‑1 — —
Why sufficient / why not (one line): a Tier‑1 argument about full replaceability without loss of the security/incentives model is required.
Conflict note (if any): —

Evidence (table)

Tier	Source	What it proves
Tier‑1	https://origintrail.io/documents/Verifiable_Internet_for_Artificial_Intelligence_whitepaper_v3_pre_publication.pdf	dRAG and the “Verifiable Internet for AI”; the DKG and Knowledge Assets; NFT ownership and onchain proofs (Merkle digests); TRAC utility (publishing fees, staking, delegation, slashing).
Tier‑1	https://origintrail.io/get-started/trac-token	TRAC token: non‑inflationary fixed supply 500M; launch 2018; multichain addresses; scenarios (publishing assets, collateral, delegation).
Tier‑1	https://docs.origintrail.io/	DKG/engine documentation (navigation on architecture/nodes/deployment).
Tier‑1	https://github.com/OriginTrail/dkg-engine/releases	releases/changes of the DKG engine component.
Tier‑1	https://github.com/OriginTrail/dkg-engine/security	security advisories.
Tier‑1	https://docs.origintrail.io/contribute-to-the-dkg/bounties-and-rewards/general-bug-bounty	the bug bounty program (Trace Labs).
Tier‑1	https://etherscan.io/token/0xaa7a9ca87d3694b5755f213b5d04094b8d0f0a6f	the onchain fact of the TRAC ERC‑20 and the contract address.