zk V e r i f y ✓

@ZKVProtocol · joined 09 Apr 2024

The most efficient modular layer optimized to verify zk proofs. Developed by @HorizenLabs Join our community → https://t.co/4YmJ1VPSBd

98 866Followers

242Following

4 173Posts total

17.6KViews on collected posts

Latest posts

zk V e r i f y ✓@ZKVProtocol3 Sep

You can't cryptographically prove an AI gave you a good answer. But you can prove the work happened as claimed. That's where $VFY enters the stack. ⚡ https://t.co/dIo5wF3Uz7

2K views · 21 likes · 4 reposts · 1 replies Open on X →

zk V e r i f y ✓@ZKVProtocol2 Sep

An AI agent can farm 10,000 reviews and still have zero reputation worth trusting. The missing layer: verifiable reputation. The agent economy needs receipts. $VFY ⚡ https://t.co/HHCpQzVZvA

2.2K views · 16 likes · 2 reposts · 0 replies Open on X →

zk V e r i f y ✓@ZKVProtocol2 Sep

@ZKVProtocol 👏 17 views · 0 likes · 0 reposts · 0 replies Open on X →

zk V e r i f y ✓@ZKVProtocol1 Sep

@ZKVProtocol verifiability is the moat 💯 62 views · 0 likes · 0 reposts · 0 replies Open on X →

zk V e r i f y ✓@ZKVProtocol1 Sep

130+ minds in the room diving into one of AI's biggest rabbit holes: How do we trust agents without blindly trusting them? 2.8K views · 57 likes · 43 reposts · 9 replies Open on X →

zk V e r i f y ✓@ZKVProtocol31 Aug

AI agents can do the work. but can we verify how they did it? last saturday, i spoke about Verifiable AI Agents with 130+ students at Microsoft Gurugram. started with the shift to agentic AI, then went into the trust problem. i also talked about cryptography, ZK proofs for htt

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5.3K views · 49 likes · 4 reposts · 11 replies Open on X →

zk V e r i f y ✓@ZKVProtocol27 Aug

Public DeFi order queues & visible liquidations make every trade an easy target for front-running bots 🎯 Moving orders into dark pools hides data, but loses verification. base:0xa749de6c28262b7ffbc5de27dc845dd7ecd2b358 verifies position proofs directly onchain. fully https://t.

2.8K views · 23 likes · 3 reposts · 2 replies Open on X →

zk V e r i f y ✓@ZKVProtocol26 Aug

Permissioned pools force full identity leaks for single-data checks. zero-knowledge proofs verify claims without handing over underlying paperwork. $VFY validates identity proofs directly onchain. apps get the answer, you keep your data ⚡ https://t.co/FKafBztnyX

2.4K views · 14 likes · 3 reposts · 3 replies Open on X →

Against accounts of the same size

8 posts from the last 90 days, next to the 10K–100K follower range. below its peers on both reach and engagement.

Median views2 281this account954median for 10K–100K

Reach, %2.31%this account3.34%median for 10K–100K

Engagement, %0.92%this account1.90%median for 10K–100K

Metric	This account	Median for 10K–100K	Ratio
Median views per post	2 281	954	2.39×
Reach (views ÷ followers)	2.31%	3.34%	0.69×
Engagement rate	0.92%	1.90%	0.49×

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

2.4K26 Aug

2.8K27 Aug

5.3K31 Aug

2.8K1 Sep

172 Sep

2.2K

2K3 Sep

Last 8 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.84%26 Aug

1.01%27 Aug

1.28%31 Aug

3.91%1 Sep

0.00%

0.00%2 Sep

0.83%

1.27%3 Sep

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.90%.

What the audience does

Likes65.9%180 in total

Reposts21.6%59 in total

Replies9.5%26 in total

Quotes1.5%4 in total

Bookmarks1.5%4 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.