Verona ✓
@verona_dev · joined 20 Mar 2021
The Intelligence Layer for AI. Verified facts you own, reusable by any agent. Leveraged by 150+ brands like Uber, Nike & backed by $36M from Multicoin, Circle.
627 072Followers
58Following
6 318Posts total
241.4KViews on collected posts
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Behind the Scenes of AI: who verifies, who pays, who trains.
On Sep 17 we're hosting a night in Seoul with @GoKiteAI, @pieverse_io, @openroboto and @Hippo_Protocol, powered by Aegis Ventures. Five teams, five sessions, Chuseok food and a raffle.
Doors at 7PM KST, Spark Plus htt
115 views · 5 likes
· 3 reposts · 2 replies
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Verona proves what's true. Pulsar moves the money.
@PulsarMoneyApp is bringing its AI companion and points program to Verona. When agentic payments land in the app, the companion will decide on verified facts, and every point will be one the user can prove. https://t.co/Igg4sySk
11.4K views · 62 likes
· 20 reposts · 18 replies
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@verona_dev @ATBASHai Enterprise deploying agent can now feel secure of there agent usage.
32 views · 1 likes
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Verona proves what's true. Atbash enforces what's allowed. That's an agent you can put in production.
Read More: https://t.co/V8nKkMG2vQ
479 views · 12 likes
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Put the two together and you get an agent that knows what's true and can't act on what's not allowed.
Verona handles everything before the action. Atbash handles the action itself and the record it leaves behind. There's no gap between them for a mistake to fall through.
487 views · 13 likes
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Capability was never the bottleneck. Trust was.
And the failures that hurt are the ones you can't reverse. The transfer already cleared. The deploy already went out. Those are the moments Atbash on Verona exists for.
265 views · 14 likes
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The timing isn't an accident. Enterprises are deploying agents faster than they can govern them, and the numbers say so.
McKinsey surveyed about 500 organizations this year and nearly two thirds said security and risk is the top barrier to scaling agents. VentureBeat surveyed
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That record is the part people underestimate.
Months from now, when a regulator or a customer asks why an agent did what it did, the answer is already written down. Nobody has to reconstruct it from logs.
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Atbash is the second question.
It sits between the agent and the tools it can reach. You set the red lines. When the agent is about to cross one, Atbash blocks it before anything happens, and when it lets an action through, it writes down why. Every decision leaves a record that
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Verona is the intelligence layer for AI, and that's the first question.
We verify a fact once at its source, and the user owns the proof. Any agent they authorize can reuse it without ever seeing the raw data.
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So trust in an agent comes down to two questions. Is what it's working from true? And is what it's about to do allowed?
Most of the industry is answering the first one. The incidents keep coming from the second.
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The agents being built today are not short on intelligence. They can reason and plan as well as most people.
What they can't do is stop themselves. An agent with all the right information will still move money it shouldn't or ship code it shouldn't, because nothing in the loop
1.1K views · 24 likes
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Verona proves what's true. @ATBASHai enforces what's allowed.
Atbash is bringing its security layer to agents on Verona. Before an agent does anything it can't undo, that action gets checked. This is the piece the agent stack has been missing. https://t.co/n0sVVE7DMt
13.9K views · 126 likes
· 80 reposts · 82 replies
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We're making AI intelligent.
Our goal is simple. Let people believe what they see online.
Try ero today: https://t.co/luW0VnElKF
4.5K views · 59 likes
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Zero-knowledge proofs power all of this. In plain terms, it's a way to prove you know something without showing what it is.
Read our litepaper to know more: https://t.co/Bp2aEi5Tij
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Verona receives a share of revenue from the use cases and applications it powers, because the network succeeds when those applications succeed.
Verona earns revenue today, and that revenue will contribute to a programmatic buy-back-and-burn.
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If you hold $XION, you already hold $VERONA.
Same contract, 1:1, nothing to migrate. The name and ticker updates will roll out across explorers and exchanges over the coming days.
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$VERONA is the native network token powering the intelligence layer.
It pays for execution under the hood, coordinates access and security, and accrues value from verified activity (i.e., revenue) on the network.
Soon, there will be a native stablecoin.
2.3K views · 45 likes
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The first thing you can do today on Verona is use 'ero' by @earnos_io
ero pays you real money for verified actions online. You log in, share only what you choose to, and get rewarded directly by brands.
2.6K views · 47 likes
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Prove anything once and reuse it anywhere. Apply for a car loan, rent an apartment, or refill a prescription.
Truth is valuable, and in a world run by agents, being able to reuse it without handing it over is everything.
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Agents need provable information to act and can’t store sensitive data.
Verona makes user-verified data portable, private, and programmable, so agents can transact on information the user actually owns.
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Today, XION becomes Verona, the intelligence layer for AI.
This comes alongside our flagship's launch of 'ero' and its $18.5M fundraise.
For five years, we've been building an internet people can believe in. Now, we're doing the same for AI. https://t.co/pbekJmnefy
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2:27
Against accounts of the same size
24 posts from the last 90 days, next to the 100K–1M follower range. reaches fewer people than peers, but engages them much harder.
Median views1 688this account5 486median for 100K–1M
Reach, %0.27%this account1.78%median for 100K–1M
Engagement, %2.16%this account1.17%median for 100K–1M
| Metric | This account | Median for 100K–1M | Ratio |
|---|---|---|---|
| Median views per post | 1 688 | 5 486 | 0.31× |
| Reach (views ÷ followers) | 0.27% | 1.78% | 0.15× |
| Engagement rate | 2.16% | 1.17% | 1.85× |
Others in this range → Compare with another account → How these benchmarks are built →
Growth & engagement
How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.
Views per post
13.9K9 Sep
1.1K
414
312
284
274
253
265
487
479
32
11.4K10 Sep
11K11 Sep
11514 Sep
Last 14 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.
Engagement rate per post
2.08%9 Sep
2.34%
3.86%
5.13%
5.63%
5.47%
5.93%
5.66%
2.87%
2.51%
3.12%
0.88%10 Sep
0.73%11 Sep
8.70%14 Sep
Reactions — likes, reposts, replies and quotes — divided by views. Median for 100K–1M accounts is 1.17%.
What the audience does
Likes64.5%1 338 in total
Reposts15.1%314 in total
Replies16.1%334 in total
Bookmarks4.2%88 in total
Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.
The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.
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