CryptoEssie

Here to learn about all things Crypto and AI. $TRAC $FET. Trying my best to grow old disgracefully. Seeking intellectual stimulation!

[OriginTrail @origin_trail]

🆕Imagine hundreds of agents working in parallel, handing off to one another and building on each other's work.

Every finding becomes a cryptographically anchored Knowledge Asset: verifiable, permanent, owned by the publisher, and queryable by any agent on the network.

Enter Decentralized Knowledge Graph v9, already powering AI agent swarms to be:
→ up to 60% faster
→ up to 40% cheaper

than markdown handoffs.

The advantage compounds as the swarm grows.

Build something exciting—or simply run a hello-world OriginTrail multiplayer game to try it!

[Žiga Drev @DrevZiga]

This is immensely important, not only for training LLMs, but because Karpathy just showed the cleanest example of the agent loop that’s about to eat everything…

…and it maps perfectly onto @origin_trail’s verifiable context graphs:
1. Human writes an emergency action plan (e.g., “build a comprehensive pandemic preparedness and realtime response mechanism, using high-quality, interoperable data combining fast-learning disease modelling, early warning and outbreak prediction, so that health responders, and policymakers can act quickly”)
2. Agent autonomously experiments across the OriginTrail DKG - spawning new context nodes, linking verifiable claims, running integrity checks
3. Clear metric (verifiability score + query precision + compliance coverage) decides what stays and what gets pruned
4. Repeat 100× overnight on a feature branch of the knowledge graph

The person who figures out how to apply this pattern to real-world OriginTrail use cases, like pharma cold-chain integrity, circular economy material twins, ESG reporting graphs, robotics and manufacturing, instead of just ML research… is going to build something massive!!!

The code is almost irrelevant.
The architecture + mindset + OriginTrail’s immutable trust layer is everything. 🚀

[Žiga Drev @DrevZiga]

At 2 billion Knowledge Assets on the @origin_trail network - driving trust across dozens of real-world sectors - we are entering a new epoch of growth.

For nearly a decade, SaaS enterprise adoption was the primary driver of the Decentralized Knowledge Graph: supply chains, compliance, manufacturing, credentials, IP protection.

Now the center of gravity is shifting.

The demand for hyperconnected context graphs is accelerating - not just for enterprises, but for AI agents.

Agentic AI systems don’t just need data.

They need verifiable memory.

They need observable decision traces.

They need cryptographic provenance.

And their demand for trusted context may soon eclipse that of traditional SaaS platforms.

2 billion Knowledge Assets was the enterprise chapter.

The next billion will be written by agents.

A new growth curve is forming - where the DKG becomes the backbone for accountable, memory-enabled AI at internet scale.

On trac(k) toward the age of agentic intelligence!

[OriginTrail @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 events, research outputs, and decision traces into a shared, queryable context graph.

And this isn’t theoretical.

→ In Switzerland, powering rail safety with partners like Swiss Federal Railways - helping ensure trusted data flows in critical train infrastructure.
→ Supporting compliance covering over 40% of US imports, including work with Walmart - bringing transparency to global supply chains.
→ Contributing to reliable aerospace and manufacturing traceability across Europe.
→ Helping protect architectural and cultural heritage through trusted provenance of restoration materials.
→ Enabling delivery and verification of donated medical treatments in emerging markets - ensuring the right medicine reaches the right patient.
→ Harmonizing import/export data post-Brexit — supporting trusted cross-border trade frameworks.
→ Delivering “grain-to-glass” transparency in Irish whiskey supply chains.
→ Anchoring 200,000+ training certificates for global auditors - verifiable credentials at scale.
→ Powering DeSci initiatives for trusted medical records - bringing reproducibility and provenance to scientific knowledge.
→ Enabling humans to trust AI agents - by giving them verifiable memory and observable decision traces.
→ Tackling illicit content at internet scale through persistent, cryptographically verifiable evidence trails.
→ Protecting intellectual property in the age of generative AI - anchoring authorship and content provenance.

2 billion Knowledge Assets form more than a graph.
They form a collective memory infrastructure for humans and machines.

And this is just the beginning.

As agentic AI scales, every agent will need memory.

Every decision will need provenance.
Every interaction will need traceability.

The Decentralized Knowledge Graph is positioning itself as the verifiable memory backbone for trillions of AI-driven interactions.

Trust the source.

[CrediBULL Crypto @CredibleCrypto]

$TRAC is objectively undervalued vs its "AI" peers when comparing revenue to current marketcap.

All revenue generated by @origin_trail is passed on to $TRAC stakers and node operators, and the token has ZERO inflation (fully circulating).

If $TRAC was trading at the same MC/Rev ratios as it's peers, it would be priced at:

ICP- $1.32
FET- $1.92
FIL- $2
NEAR- $3.26
TAO- $3.70
RNDR- $3.56
GRT- $5.75

It currently trades at .32.

[Žiga Drev @DrevZiga]

Grok now generates about 6,700 sexually suggestive images (including CSAM) per hour, compared to 79 new such AI images per hour on other top websites.

Fortunately, @umanitek emphasizes gathering data from @X on @origin_trail to protect its users.

https://t.co/zCW0K4iqfb

[Saganism @Saganismm]

Carl Sagan’s prediction about America, made 31 years ago.

[OriginTrail @origin_trail]

“We’ve solved the model, but we have not solved the data at all.”

@Shawmakesmagic, creator of @elizaOS, on why AI progress depends less on models – and more on scientific rigor and trusted data.

[CrediBULL Crypto @CredibleCrypto]

The stats:

- Zero token inflation.
- 100% of supply circulating.
- $4.8M of revenue generated in 2025 (+28% YoY).
- 100% of revenue generated paid to stakers/node operators.
- 20% of total supply staked.

Some TA to go with the stats:

Watching this LTF range here, if we get another dip down into our HTF accumulation zone, I will scrounge together whatever spare change I can find to make another (likely final) spot buy of $TRAC.

[Žiga Drev @DrevZiga]

@otnoderunner In the grand scheme of things, this is the only comparison that matters.

Overcoming a chasm in trust and user sovereignty with systems that govern our lives.

Ergo @origin_trail $trac vs the likes of @PalantirTech $pltr

[CrediBULL Crypto @CredibleCrypto]

Today, $TRAC officially hits the 100M mark for tokens staked- that is 20% of all the $TRAC that will ever exist is now being staked.

Those that are staking their $TRAC and those that are running nodes earn 100% of the revenue generated from data storage on the @origin_trail DKG (average 7-10% APR).

1. Real use cases
2. Real customers
3. Real yield
4. No inflation
5. No dilution

That's $TRAC.

[CrediBULL Crypto @CredibleCrypto]

Honestly if I could sum up the argument for $TRAC in a single sentence- it would be this:

"The more AI is adopted in the world, the more $TRAC is needed."

$TRAC is a utility token that is bought by and used as payment for clients that want to store data on the DKG (decentralized knowledge graph) in order to fight misinformation, deepfakes and AI, and in general protect data authenticity on the internet.

And because there is ZERO inflation on the token and the supply is already fully circulating, as demand grows, so naturally will price.

This is econ 101- when demand is RISING and supply is FIXED, price goes UP.

[CrediBULL Crypto @CredibleCrypto]

And for the numbers guys:

At it's very core and at current prices, $TRAC earns stakers an average of around 7-10% APR, which FULLY comes from money being paid by customers to add/store data on the network aka "real" yield.

From a traditional investment perspective, this almost establishes a "floor" price at current usage levels.

Trad-fi investors can park their money in $TRAC at current levels and easily earn a solid annual return from staking yield alone, without factoring in the potential upside of investing in an asset that will only benefit from speculation driven upside within the crypto space as a whole.

At the end of the day (and in the current cycle) it is ultimately speculation that is the driving force behind crypto today and it's this speculation that will drive some crypto assets to obscene valuations in the coming months.

HOWEVER when you're dealing with an ever-increasing pool of crypto assets- most of which have zero reason to exist- it's the ones that DO have a strong fundamental base that are ultimately most likely to win the attention of speculators over time because this is what separates tokens like $TRAC from the other tens of thousands that are essentially vaporware.

The ability to actually generate a revenue/profit for token holders by selling a real product to real customers is something people from the outside looking in WILL take notice of.

It is simply a matter of time.

[OriginTrail @origin_trail]

𝙸𝚗 𝚝𝚑𝚎 𝚊𝚐𝚎 𝚘𝚏 𝙰𝙸 𝚑𝚘𝚠 𝚍𝚘 𝚠𝚎 𝚔𝚗𝚘𝚠 𝚠𝚑𝚊𝚝 𝚒𝚜 𝚝𝚛𝚞𝚎?

𝙼𝚎𝚝𝚌𝚊𝚕𝚏𝚎 𝙲𝚘𝚗𝚟𝚎𝚛𝚐𝚎𝚗𝚌𝚎 𝙲𝚑𝚊𝚙𝚝𝚎𝚛:
𝚂𝚌𝚊𝚕𝚒𝚗𝚐 𝚝𝚛𝚞𝚜𝚝 𝚒𝚗 𝚝𝚑𝚎 𝚊𝚐𝚎 𝚘𝚏 𝙰𝙸

𝙳𝚎𝚌𝚎𝚖𝚋𝚎𝚛 3

[CrediBULL Crypto @CredibleCrypto]

Something tells me this activity is going to continue to climb a bit higher in the coming weeks...

$TRAC

[CrediBULL Crypto @CredibleCrypto]

You have to zoom out folks.

What $TRAC has done so far is literally nothing. We are still sitting in the HTF accumulation/buy zone.

If this isn't a coin "that hasn't pumped yet" then I don't know what is.

[Žiga Drev @DrevZiga]

•⁠ Oxford PharmaGenesis news (clients 8/10 pharma giants)
•⁠ @Microsoft & @origin_trail powering enterprise AI
•⁠ Closing in on 100 million $trac stakd (20% of FDV)
•⁠ New DKG node (Umanitek 1) staking cap reached
•⁠ @umanitek building largest content library
•⁠ New product releases in making...

Trace ON!

[OriginTrail @origin_trail]

https://t.co/wqKOpWMdyS

[CrediBULL Crypto @CredibleCrypto]

I am a coin.

I was created in 2018.

1. I am currently trading 90% below prior ATH's in 2021, but my total supply remains exactly the same since then (zero inflation).

2. I have a capped supply which is already fully circulating, meaning I have ZERO future emissions/inflation scheduled (with the exception of 16% of my supply which has been locked in my treasury since 2018, for future project needs/growth).

3. I generate more revenue/yield than most other "better known" projects in the same niche, despite having a current market cap that is a fraction of them. (For example, I generate nearly as much revenue as $NEAR, despite having 1/20th the marketcap).

4. I pass on 100% of the "real yield" that I generate (from real users who are currently paying to use my services) to stakers/node operators that secure the network.

5. ~20 of my total supply is currently staked and earning this real yield.

6, The service that users are paying me to use solves many things, including a rapidly growing problem that we can see examples of every single day on this platform (X) and other places on the internet (a problem which is only going to become a bigger issue moving forward with the growth of AI).

Who am I?

[CrediBULL Crypto @CredibleCrypto]

I am $TRAC.

And just like I tweeted about it the last time it hit this HTF accumulation zone 2-3 months ago (here: https://t.co/GfQB8Vsc1i) you will probably see me tweeting about it again when it revisits this zone because you can't go wrong with spot buys at these levels on a long enough time horizon imo.

A lot of charts look like this atm, not a lot of them have zero inflation and an actual working product with users that generate real yield for token stakers AND are relatively undervalued by this metric vs it's peers.

You can learn more about $TRAC by visiting @origin_trail.