Crypto taught us to hold our own keys. Intelligence is next. 🔐

AI is accumulating our research, decisions, ideas and years of context. That history becomes more valuable with every conversation.

Founder Dan Leong explores why custody will matter deeply for AI. https://yvechat.xyz/news/why-self-custody-is-coming-for-intelligence

Tools make AI more capable. They also widen the security surface.

MCP tools can represent arbitrary code execution. Tool metadata must be treated as untrusted input. Installing a local MCP server can itself execute code. YveChat's planned MCP layer is designed around per-tool permissions and explicit boundaries. Actions that write, send, purchase or authenticate require confirmation.

Capability deserves control at the point of action. https://x.com/yvechat

Your AI identity can live under your signature.

YveChat supports optional wallet authentication alongside local accounts. A wallet signature can establish identity without handing custody of that identity to a conventional account system.

That choice carries an explicit responsibility too. Signature identity has no recovery path. Wallet phishing resistance still depends on the wallet itself.

Control becomes meaningful when its consequences are stated clearly.

Self-custody transfers responsibility with control.

Run your own AI infrastructure and operational responsibility moves with it. YveChat treats this as part of sovereignty itself.

Control has weight. That is precisely why it matters.

One successful AMA. Two founders. Plenty to unpack. 🔥

Dan & Alvis went deep on owning your AI, YveChat Engine, local models, provider choice, agent permissions and the roadmap ahead.

The community brought the questions. Here's the recap if you missed it! https://yvechat.xyz/news/community-ama-recap-own-your-ai-and-what-comes-next

One thread can become neutral ground between models.

YveChat is building toward a workspace where context can carry as you move between local and frontier models. The foundation is already taking shape in layers: Ollama-served local models are available. OpenAI-compatible endpoints are experimental. Full hosted-provider credential management is planned.

Your context stays centered on you.

$YVE remains pre-generation.

No contract has been deployed. No sale is open. Token figures remain provisional.

The intended role is already defined: $YVE coordinates the layers beyond the user's own machine, including the scaling tier, gateway, marketplace, future compute settlement and governance.

Any current offer claiming to sell $YVE is fraudulent https://yvechat.gitbook.io/wp/resources/verified-links

YveChat is the infrastructure powering sovereign AI on user-owned machines.

382 YveChat Engines alive.
241 active daily.
4,850 inferences run every day.
20.8M tokens generated locally across 31 models.

The demand for local AI cannot be overstated!

Dashboard: https://yvechat.xyz/#achievements
Methodology: https://yvechat.gitbook.io/wp/res/method

Your AI history can live on hardware you own.

YveChat Engine persists conversations to a SQLite database on your own disk.

Threads stay on user-controlled infrastructure, with user-configurable external storage planned as the architecture expands.

Six digits connect the web workspace to your machine.

YveChat pairing uses a one-time code you approve locally, with origin binding, hashed storage, expiry and revocation.

Configured origins are explicit. Wildcards are refused.

Access can disappear. Custody stays in your hands.

YveChat is built around direct control of your models, conversations, compute, credentials, and identity. The infrastructure that determines access sits within your boundary.

Your models. Your machine. Your workspace.

Sometimes building YveChat is two people asking the same question from completely different directions. 😄

Dan thinks ownership. Alvis thinks infrastructure. They debate, challenge each other and occasionally create more work for Alvis.

Meet the brains behind YveChat. https://yvechat.xyz/news/the-conversations-behind-yvechat

In just 5 days, Total Engines grew 66%.

Engines alive: 382 → 629
Daily active Engines: 241 → 400
Daily inferences: 4,850 → 9,039
Attesting wallets: 208 → 270

More people putting their own machines to work. Humbled by the growth!

Dashboard: yvechat.xyz/#achievements
On-chain Transparency: https://yvechat.gitbook.io/wp/res/method

Six digits connect the web workspace to your machine.

YveChat uses a one-time pairing flow between the hosted Workspace and the local Engine. You approve the introduction yourself on your machine. Pairing includes origin binding, hashed storage, expiry and revocation. The origin policy accepts configured origins and refuses wildcards.

Once paired, the browser has a controlled path to the Engine operating locally. A small interaction establishes a very important trust boundary.

Local AI is getting seriously capable. Its infrastructure is the next frontier. ⚙️

CTO Alvis Sim breaks down Ollama, self hosted data, model choice, agent permissions and why YveChat Engine exists.

The models are moving fast. Here is what needs to catch up https://yvechat.xyz/news/local-ai-needs-better-infrastructure

Longer context has a physical cost.

With Ollama, memory demand scales with parallelism and context. More simultaneous workloads and larger context windows require more resources.

Running intelligence yourself means seeing the real hardware economics underneath it.

Local AI can grow beyond a single desktop runtime.

YveChat's experimental OpenAI-compatible adapter supports vLLM for users with suitable GPU infrastructure, extending the same workspace toward independently operated model-serving environments.

Your machine already has an AI environment. YveChat Engine discovers it.

Dynamic model discovery identifies available local runtimes and models, turning infrastructure running on your own hardware into something the workspace can understand and use directly.

A wallet signature has a clear boundary.

SIWE authenticates control of a wallet. Phishing resistance depends on wallet security, wallet-derived encryption lacks a standard, and signature identity has no built-in recovery.

Sovereignty works best when its limits are explicit.

Sovereignty covers the entire AI workspace.

Compute. Data. Access. Identity. YveChat places each layer within the user's control, from local runtimes and storage to pairing and optional wallet signatures.

Read the full architecture https://yvechat.gitbook.io/wp

Sovereign inference has a real hardware layer.

Local GPU acceleration can be driver-sensitive. vLLM requires suitable GPU infrastructure.

Hardware, drivers, runtimes, and context limits become visible parts of the stack when you operate the intelligence yourself.