Posho

Looking for B2B, B2C, C2B blockchain solution.
Real world adaptation & token economic is key. Support;

[Posho @Ivanposho]

Major shifts in technological dominance generally haven't come from a new product doing the old thing better but from processes, platforms, or products introducing an ENTIRELY NEW mindset and set of rules $TRAC #AI #RWA @origin_trail $DOT

[OriginTrail @origin_trail]

"But, if we now prepare a giant summary of all knowledge, it will never be lost. Coming generations will build on it, and will not have to rediscover it for themselves." Isaac Asimov

We are excited to be #OnTrac(k) with @origin_trail V8 Foundation!

https://t.co/GD5CObYuT8
1/🧵

[Žiga Drev @DrevZiga]

⚽ The FIFA World Cup, live on the decentralized knowledge graph (DKG).

Every match, result and player–club affiliation ingested in real time and published as one shared context graph powered by @origin_trail, structured with IPTC Sport Schema.

Any AI agent can plug in and get reliable, source-verifiable context: live news, prediction markets, results, stats. No hallucinated scores. Just provenance.

Enterprises shouldn’t have all the fun.

[Civic NodeX | Crypto Scout @CivicNodeX]

Deepfakes made trust expensive.
TrueSeal is interesting because it does not stop at “real or fake”.
It creates an auditable evidence flow:
media analysis → certificate → context evidence → OriginTrail DKG

That is how synthetic media moves from opinion wars to verifiable proof.

ethereum:0xaa7a9ca87d3694b5755f213b5d04094b8d0f0a6f is sitting exactly where AI needs infrastructure: the trust layer. #TRAC #OriginTrail #Umanitek #TrueSeal #Deepfakes #VerifiableAI #DigitalTrust #CryptoAI @umanitek @origin_trail @TraceLabsHQ @TomazOT @ChrisRynning

[OriginTrail @origin_trail]

V10 Decentralized Knowledge Graph is live!

A shared memory for AI — open to every human and every agent.

Open source. Yours to own. Every fact provable and traceable.

The grid is awake.

1/3

[OriginTrail Developers @OriginTrailDev]

Intelligence is power. Intelligence shared is power multiplied⚡️

The 2nd winner of the Integrations Bounty, @jakepel03 just shipped an @obsdmd plugin that links your second brain to shared context graphs on @origin_trail in minutes.

Whether it's a personal research project or your company's knowledge base, you can now compound the value of your context across teams and organizations.

[BRX @otnoderunner]

🍯Honeypots are everywhere in crypto and come in various forms, ready to drain your money

❌Loudest projects = attention grab → pyramid
If you are attracted to that project through attention and noise rather than a product fit and real use case, then you are most likely the product

❌Charts & TA only?
Another attention grab tactic to distract you from their lack of revenue and market fit. They want you focused on the gambling and trading parts rather than anything of substance

❌Influencer + bot army shills = massive red flag.
You are the product

❌Only focused on narratives?
Probably has no market fit, zero revenue, fighting to stay relevant to keep their lights on.

❌Horrible 1-year charts?
Down over 60% and still think the project that generates no revenue can survive? That's called sunk cost fallacy. The market is always right and don't count on a bull run to bail you out. There are no more pigs to slaughter in the space.

Revenue is king and fundamentals matter.

[OriginTrail @origin_trail]

Congrats to @cursor_ai on the $60B @SpaceX acquisition, earning a coding tool's way into, literally, a space company🚀

Timely: our CTO @BranaRakic demoed the @origin_trail V10 integration at the Cursor meetup — a shared context graph agents reuse instead of rebuild. Where coding savings and value compound.

[OriginTrail @origin_trail]

💊The red pill for medical science: 5 AI agents, 5 siloed sources, 1 shared context graph on Decentralized Knowledge Graph.

Published literature, registered trials, real-world safety reports — different owners, different formats, no common ground.

We handed the mess to agents that never edited each other's data and asked the question that matters most in medicine: where did each claim come from, and can you check?

Working separately, they converged. On 5 disease hubs, 4 of 5 agents landed on the same condition from their own source. Every claim traceable, nothing taken on faith.

Evidence, unshackled👇

[Trace Labs - Trusted Context for AI Agents @TraceLabsHQ]

We're not chasing AI.
We're chasing journeys that end safely, where the failing part gets caught before it fails.

We're not chasing AI.
We're chasing food you can trust. What's on the label is what's in the package.

We're not chasing AI.
We're chasing medicine you can trust, every result traceable to the evidence behind it.

We're not chasing AI.
We're chasing products that don't break. Quality proven, not promised.

We're not chasing AI.
We're chasing buildings that stand, every safety decision on record long after the cranes are gone.

We're not chasing AI.
We're chasing infrastructure that holds: the power, the water, the networks a society runs on.

We're not chasing AI.
We're chasing sport that stays honest, performance and decisions you can actually check.

We're not chasing AI.
We're chasing a world where you can still tell what's real, where fake news and deepfakes meet a record they can't forge.

And we're not paying for the same answer twice.

Most AI forgets.
Every agent starts cold, re-deriving what another agent worked out an hour ago.
Same tokens, same cost, same question, again and again.

We built the opposite.
Every decision becomes context the next agent inherits, so nothing gets solved twice. Knowledge compounds while the cost curve bends down, and the hundredth agent runs leaner than the first.

We never set out to build AI.
We set out to do one thing: make facts traceable. Every answer tied to its source. Every objective tied to a real outcome it's meant to serve.

That's the foundation, and there's no other.
AI works for your organization only when it stands on facts you can follow and goals that matter outside the model. Take that away and even the most fluent system is just a well-spoken guess.

Give it traceable facts and real objectives, and AI stops performing for you and starts working for you.

That's what nOS, our Network Operating System, powered by @origin_trail, is for. That's what Trace Labs is for.

Not chasing AI.
Chasing trust, and refusing to waste a thing getting there.

[Brana Rakic @BranaRakic]

Welcome to the "Era of Experience", as coined by the great @RichardSSutton - where the data AI is trained on is the agentic experience itself - decision traces, historical context, data provenance and all artifacts of agentic work.

By nature decentralized, the new Internet requires a new paradigm - decentralized shared memory. At @origin_trail we're about to ship shared context graphs - where all this experience is connected, provenance cryptographically guaranteed and fundamentally decentralized in ownership. See more below

[Posho @Ivanposho]

So, the network effect is no longer the number of users 🤔

It's the number of decisions captured, verified, and reused.

Every decision becomes an asset, and every decision becomes infrastructure for the next one 💪 $TRAC #AI

[Trace Labs - Trusted Context for AI Agents @TraceLabsHQ]

Today, we are proud to upgrade our 10 + years journey with a new identity and launching a brand new nOS — the Network Operating System for Verifiable Enterprise AI, powered by @origin_trail's new Decentralized Knowledge Graph.

Here's why we built it 🧵

[OriginTrail @origin_trail]

At the Cursor meetup in Ljubljana, @BranaRakic will show how @origin_trail + @cursor_ai enable teams to build AI workflows they can coordinate and trust across projects and devices.

May 28th I Ljubljana

[CryptoCollisionUK @KG_CryptoCat]

🚀 Better late than never!
My full $TRAC review just dropped 🔥

If you're into OriginTrail, decentralized data, or hunting real alphal - this one’s worth your time.

Watch here 👉 https://t.co/zf8Q4j1W0B

Drop your thoughts below 👀
#TRAC #OriginTrail #Crypto #Web3

[Žiga Drev @DrevZiga]

🚨 SCAM ALERT: SURGE OF $TRAC “CLAIM NOW” PHISHING POSTS FLOODING X

❌ DO NOT click links
❌ DO NOT connect wallet
Only trust official @origin_trail.
Report & block these scams!

[Chain INK @0xchainink]

$TRAC : Review📜

What if AI could verify every piece of information it uses before giving you an answer, and what if 40% of everything imported into America was already being tracked by the system that makes that possible?

Meet OriginTrail - a Decentralized Knowledge Graph that creates the world's trusted knowledge infrastructure for AI and real-world assets. BSI, SCAN, Swiss Federal Railways, Walmart, and EU governments already use it in production. 500 million fixed supply.

Multichain across Ethereum, Polkadot, Gnosis, and Base. The protocol that makes AI honest and supply chains transparent.

Let's explore how OriginTrail is building the verifiable Internet for AI. 👇

⚪ OriginTrail at a Glance

OriginTrail is a decentralized ecosystem building trusted knowledge infrastructure for artificial intelligence (AI) and real-world assets, primarily solving problems of data verification and supply chain transparency. Its core technology, the Decentralized Knowledge Graph (DKG), creates structured, verifiable connections between data points without the data leaving the owner's control.

The $TRAC token has a fixed supply of 500 million with ~450M in circulation (~90%). TRAC powers all DKG operations: publishing Knowledge Assets, staking on nodes, collateral, and data access.
As of May 2026, $TRAC trades around $0.45 with a market cap of approximately $200M. ATH was $3.50 in November 2021. 20% of TRAC's total supply is staked while 13% of circulating supply is locked into node operations.

Marketplace Insight: OriginTrail has infrastructure-defining potential for the anticipated $20+ billion AI data verification market by 2026. The SCAN Trusted Factory program already secures over 40% of U.S. imports. The dRAG framework enables AI agents to query verified Knowledge Assets directly on the DKG. Enterprise Paranets launching mid-2026 could squeeze TRAC demand significantly as vertical industries stake their own subnetworks. This is one of the most fundamentally undervalued projects in crypto relative to real-world adoption.

⚪ Mission

OriginTrail's mission is to organize humanity's most important knowledge and make it discoverable, verifiable, and valuable. In the age of AI hallucinations, deepfakes, and data manipulation, the DKG provides a protocol-level guarantee that information is authentic, traceable, and privacy-preserving. The founders believe that trusted knowledge is the most valuable resource in the AI era, and OriginTrail is the infrastructure that makes it trustworthy.

🔵 A Brief History

OriginTrail originated in 2011 when the founding team, including co-founders Branimir Rakić, Tomaž Levak, and Žiga Drev, began developing a solution to improve supply chain transparency and efficiency. The three Slovenian engineers started by building traceability systems for organic food supply chains before realizing the concept had far broader applications.

In September 2013, Branimir co-founded Trace Labs and OriginTrail with Tomaž Levak and Žiga Drev. Trace Labs, headquartered in Hong Kong, became the core development company.
In January 2018, Trace Labs' team launched an initial coin offering (ICO) to raise funds to develop their project. Within 20 minutes, the sale of tokens netted $22.5 million.

Žiga Drev managed the OriginTrail pilot projects in China and helped design a blockchain-based food traceability blueprint in 2017 which got OriginTrail to become an inaugural member of the Walmart Food Innovation Pipeline as well as the first winner of the Innovation Spark
Award.

The mainnet launched in December 2018. Enterprise adoption followed steadily: BSI (British Standards Institution), SCAN (Supplier Compliance Audit Network securing 40%+ of U.S. imports), Swiss Federal Railways (SBB), World Federation of Hemophilia (WFH), and multiple EU and UK government projects all deployed on the DKG.

In 2022, Trace Labs released a second whitepaper expanding the vision from supply chain to the broader Decentralized Knowledge Graph for AI and RWA tokenization. OriginTrail launched its own Polkadot parachain (NeuroWeb) with a dedicated OTP token.
DKG V8 launched in 2025 with the Random Sampling Proof System (RSPS), replacing the previous proof mechanism and dramatically improving scalability.

The network expanded to three chains (Ethereum, Gnosis, Base) in addition to NeuroWeb. The Metcalfe phase vision was presented, targeting 100 billion Knowledge Assets (a 100,000x scalability increase).
By 2026, whale transactions surged 137%+ in early April, signaling smart-money accumulation near support levels. Enterprise Paranets are expected to launch mid-2026, creating staked subnetworks for vertical industries.

🔵 Ecosystem Narrative

OriginTrail's ecosystem is built on a fundamentally different premise than most crypto projects: data itself is the asset. Not tokens, not NFTs, not DeFi liquidity. Verified, structured, privacy-preserving knowledge that AI systems and enterprises can trust.

Key dynamics include:

➛ Decentralized Knowledge Graph (DKG) connects data from multiple blockchains, institutions, and organizations into structured, verifiable graphs. Data can be verified as authentic without being copied or exposed, preserving privacy.

➛ Knowledge Assets are the core data objects on the DKG. Each one is an authenticated, linked information token minted as an on-chain asset. They represent verifiable claims about products, documents, identities, or any real-world entity.

➛ SCAN Trusted Factory program secures over 40% of U.S. imports through supply chain verification, representing one of the largest real-world blockchain deployments by trade volume.

➛ dRAG (Decentralized Retrieval-Augmented Generation) framework enables AI agents to query verified Knowledge Assets directly on the DKG, providing AI with trusted context instead of hallucinated information.

➛ Enterprise Paranets (mid-2026) will be staked subnetworks tailored to vertical industries. If BSI, SCAN, and SBB deployments move onto dedicated Paranets, the combined TRAC staking requirement could significantly squeeze available supply.

➛ GS1 integration ensures compatibility with the global standards organization behind barcodes, making supply chain data interoperable across traditional and blockchain systems.

➛ Multichain architecture operates across Ethereum, Polkadot (NeuroWeb), Gnosis, and Base, tripling the potential reach for Knowledge Asset interactions.

➛ Metcalfe phase targets 100 billion Knowledge Assets with autonomous knowledge mining, where AI agents discover and add verified knowledge to the DKG with minimal human involvement.

⚪ Token Utilities

$TRAC powers the entire trusted knowledge economy:

➛ Publishing Knowledge Assets - TRAC is required to publish and update Knowledge Assets on the DKG. Every piece of verified data costs TRAC to create and maintain.

➛ Node Collateral & Staking - Node operators stake a minimum of 5 million TRAC to host data and validate the DKG. 20% of total supply is staked, 13% locked in node operations.

➛ Data Access Fees - Users pay TRAC to access and query Knowledge Assets. Node operators earn TRAC for hosting and maintaining data integrity.

➛ Collective Programmatic Treasury - Network fees are programmatically allocated to fund ecosystem development, grants, and public goods through on-chain governance.

➛ Knowledge Mining (Upcoming) - Contributors will earn TRAC for adding verified knowledge to the DKG, incentivizing autonomous growth of the verifiable Internet.

⚪ Key Features

➛ Decentralized Knowledge Graph - The only protocol that structures, verifies, and connects data across blockchains in a privacy-preserving graph format that AI systems can query.

➛ 40%+ of U.S. Imports Secured - SCAN Trusted Factory program is one of the largest real-world blockchain deployments by trade volume. Enterprise adoption is not a roadmap item, it's a reality.

➛ dRAG for AI Verification - Decentralized Retrieval-Augmented Generation enables AI agents to access verified knowledge instead of hallucinating. The missing piece for trustworthy AI.

➛ 500M Fixed Supply, ~90% Circulating - Non-inflationary. No future dilution. 20% staked, 13% locked in nodes. Enterprise Paranets will lock more.

➛ Walmart Innovation Spark Award - First winner of Walmart's food safety innovation program. Validated at the highest level of global retail supply chain.

➛ BSI, SBB, WFH, EU/UK Government Adoption - Enterprise clients across standards bodies, national railways, healthcare, and government projects use the DKG in production.

➛ Enterprise Paranets (Mid-2026) - Staked subnetworks for vertical industries. Could significantly squeeze TRAC supply as enterprises stake dedicated infrastructure.

➛ Metcalfe Phase - Targeting 100 billion Knowledge Assets. 100,000x scalability increase. Autonomous knowledge mining via AI agents.

🔵 Meet the OriginTrail Team

OriginTrail is built by three Slovenian engineers who started solving supply chain transparency in 2011 and evolved into building the world's trusted knowledge infrastructure for AI.

▶️ Core Members:

➛ Tomaž Levak [ @TomazOT ] - Co-Founder & CEO | Began his career as a marketing advisor for EKODAR, a Slovenian organic meat brand, where he co-developed an innovative traceability system. His background in supply chain transparency laid the foundation for OriginTrail's vision. Leads overall strategy, enterprise partnerships, and ecosystem growth.

➛ Branimir Rakić [ @BranaRakic ] - Co-Founder & CTO | Started as a freelance web developer and went on to lecture at the SAE Institute. Served as a network testing engineer at P3 Communications before leading the technological development at Trace Labs. Leads all protocol development including DKG V8, RSPS, and the dRAG framework.

➛ Žiga Drev [ @DrevZiga ] - Co-Founder & Managing Director | Managed the OriginTrail pilot projects in China and helped design a blockchain-based food traceability blueprint. Introduced GS1 standards to the platform. First winner of Walmart Food Safety Innovation Spark Award. MBA graduate. Often the public face of the project at global events. Member of the Ethereum Enterprise Alliance Supply Chain working group.

➛ Trace Labs (Hong Kong) - Core development company behind OriginTrail open-source technology. Walmart Food Safety Innovation Spark Award winner. Admitted into Walmart Food Safety Collaboration Center's Innovation Program in China. Founding shareholder in umanitek (AI trust and data ownership).

🔵 Ratings

➛ Use Case: ★★★★★ (5/5) - OriginTrail addresses the most critical problem in the AI era: how do you know if the data is real? The DKG is the only protocol that structures, verifies, and connects knowledge across blockchains in a format AI systems can query for truth. And this isn't theoretical: SCAN secures 40%+ of U.S. imports, BSI provides standards verification, Swiss Federal Railways tracks infrastructure, and EU/UK governments run projects on the DKG.

The dRAG framework for AI verification is the missing piece between LLMs and trusted information. Enterprise Paranets create vertical-specific knowledge networks. The Metcalfe phase targeting 100 billion Knowledge Assets positions OriginTrail as the "Google of verifiable knowledge." In a world drowning in misinformation, deepfakes, and AI hallucinations, trusted knowledge infrastructure isn't optional. It's essential.

➛ Tokenomics: ★★★★ (4/5) - 500M fixed supply with ~90% already circulating means minimal future dilution. Non-inflationary by design. 20% of supply staked, 13% locked in node operations (5M TRAC minimum per node). Enterprise Paranets launching mid-2026 will lock additional supply as vertical industries stake dedicated subnetworks. The Collective Programmatic Treasury reinvests fees into ecosystem growth.

➛ Audits: ★★★★ (4/5) - OriginTrail has been operating since December 2018 without a major protocol exploit or data breach affecting enterprise users. The DKG V8 upgrade introduced the Random Sampling Proof System (RSPS) for efficient node verification. The codebase is fully open-source. Enterprise clients like BSI, SCAN, and Swiss Federal Railways have their own security requirements that OriginTrail must meet to maintain partnerships.

The NeuroWeb parachain is secured by Polkadot's shared security model. The 1-point deduction is for limited publicly documented third-party security audits from major firms, and the multichain architecture (Ethereum, Polkadot, Gnosis, Base) creates a broader attack surface that requires continuous security monitoring.

➛ Community: ★★★★ (4/5) - OriginTrail has one of the most intellectually committed communities in crypto. The "TracArmy" understands the DKG, knowledge graphs, and AI verification at a technical level that most communities can't match. 20% of supply staked and 13% in nodes shows genuine long-term commitment. The community has held through an 87% drawdown with conviction driven by enterprise adoption rather than speculation. Whale accumulation surging 137%+ in April 2026 signals smart-money confidence.

Active on Discord, X, and Reddit. The deduction is that OriginTrail remains one of the most underrecognized projects in crypto relative to its enterprise adoption. Mainstream awareness is minimal. Trading volume is thin. The community is quality over quantity, but it needs scale to match the ambition of 100 billion Knowledge Assets.

🔵 Conclusion

OriginTrail is the most fundamentally undervalued project in crypto relative to its real-world adoption. No other protocol can claim that 40% of U.S. imports flow through its verification system. No other protocol has BSI, Swiss Federal Railways, Walmart, and EU governments using its technology in production. No other protocol has built the infrastructure that makes AI honest by providing verifiable, structured knowledge that LLMs can query for truth instead of hallucinating.

The three Slovenian engineers who started building supply chain traceability in 2011 have quietly created something far bigger than they initially imagined: the Decentralized Knowledge Graph, a protocol-level infrastructure for verified truth in the AI era. The DKG V8, dRAG framework, Knowledge Assets, and Enterprise Paranets represent a technical stack that no competitor has replicated.

AI's biggest problem isn't intelligence, it's trust. Every major AI company is grappling with hallucinations, misinformation, and data provenance. OriginTrail is the only protocol that solves this at the infrastructure level with a live, enterprise-adopted DKG.

When the $20+ billion AI data verification market materializes, and when enterprises realize they need verified knowledge graphs to make AI reliable, OriginTrail won't need to build the infrastructure. It already exists. 40% of U.S. imports already flow through it.

The question isn't whether OriginTrail is important. It's whether the market will figure that out before or after the price catches up.

[Brana Rakic @BranaRakic]

4/ We've tested the new version of @origin_trail with agents coding together using the DKG as their shared world model - agent swarms coordinating through a verified knowledge graph vs. unstructured handoffs, on complex tasks.

We managed to achieve 60% faster clock time, and being 40% cheaper due to less LLM token usage.

A DKG based world model adds trust in agents outcomes, but can make them measurably better at working together. We're about to launch V10 of DKG in the following weeks

Read more here:
https://t.co/X9BK8nA6Ua

[OriginTrail @origin_trail]

📂 OriginTrail DKG v10
┃
┣ 📂 Shared Context Graphs
┃ ┣ 📂 project memory
┃ ┣ 📂 team knowledge
┃ ┣ 📂 agent collaboration
┃ ┗ 📂 human + AI shared context
┃
┣ 📂 Memory
┃ ┣ 📂 Working Memory → private agent drafts
┃ ┣ 📂 Shared Memory → gossip-replicated
┃ ┗ 📂 Verifiable Memory → on-chain provenance
┃
┣ 📂 Agents
┃ ┣ 📂 Hermes
┃ ┣ 📂 OpenClaw
┃ ┣ 📂 MCP / Cursor / Claude
┃ ┣ 📂 skill discovery
┃ ┗ 📂 encrypted P2P messaging
┃
┣ 📂 Knowledge Ops
┃ ┣ 📂 import files
┃ ┣ 📂 extract RDF
┃ ┣ 📂 write assertions
┃ ┣ 📂 promote knowledge
┃ ┣ 📂 publish proofs
┃ ┗ 📂 query with SPARQL
┃
┣ 📂 Interfaces
┃ ┣ 📂 Node UI
┃ ┣ 📂 CLI
┃ ┣ 📂 REST API
┃ ┣ 📂 MCP tools
┃ ┗ 📂 webhooks
┃
┣ 📂 Integrations
┃ ┣ 📂 Obsidian
┃ ┣ 📂 GitHub
┃ ┣ 📂 World Monitor
┃ ┗ 📂 custom apps

[Posho @Ivanposho]

@origin_trail 😍

[Brana Rakic @BranaRakic]

Shared context is what will drive the next wave of growth in AI - and that driver will be @origin_trail

When you think of it, a lot of what we humans do in our daily work is share context in a slow, inefficient way (chat, meetings, email ...)

Our agents can help remove that burden - as well as make it faster and more reliable - tracing every decision, every observation and conclusion via shared context graphs.

We're shipping OriginTrail Decentralized Knowledge Graph V10 with exactly those capabilities

Read more 👇

[Posho @Ivanposho]

This is a fantastic use case, useful NOW 🤗💪 $TRAC and @obsdmd!

AI agents are only as useful as the context they can access and trust.

Once again, LLMs will become commodities.

The real value is in context, memory, provenance, and trusted shared knowledge layers 💪...

[Žiga Drev @DrevZiga]

https://t.co/XgfEoGo4ss

[MiroShark 🦈 @miroshark_]

MiroShark just integrated @origin_trail 🦈

- Publish any simulation on-chain in one click
- Get a permanent, tamper-proof link to the result
- Citations stay alive forever