Safe & secure Chromia's EVAL by Virtuals wallet
Take control of your Chromia's EVAL by Virtuals assets with complete confidence in the Trezor ecosystem.
- Secured by your hardware wallet
- Use with compatible hot wallets
- Trusted by over 2 million customers

Send & receive your Chromia's EVAL by Virtuals with the Trezor Suite app
Send & receive
Trezor hardware wallets that support Chromia's EVAL by Virtuals
Sync your Trezor with wallet apps
Manage your Chromia's EVAL by Virtuals with your Trezor hardware wallet synced with several wallet apps.
Trezor Suite
MetaMask
Rabby
Supported Chromia's EVAL by Virtuals Network
- Base
Why a hardware wallet?
Go offline with Trezor
- You own 100% of your coins
- Your wallet is 100% safe offline
- Your data is 100% anonymous
- Your coins aren’t tied to any company
Online exchanges
- If an exchange fails, you lose your coins
- Exchanges are targets for hackers
- Your personal data may be exposed
- You don’t truly own your coins
How to EVAL on Trezor
Connect your Trezor
Open a third-party wallet app
Manage your assets
Make the most of your EVAL
Trezor keeps your EVAL secure
- Protected by Secure Element
The best defense against both online and offline threats
- Your tokens, your control
Absolute control of every transaction with on-device confirmation
- Security starts with open-source
Transparent wallet design makes your Trezor better and safer
- Clear & simple wallet backup
Recover access to your digital assets with a new backup standard
- Confidence from day one
Packaging & device security seals protect your Trezor’s integrity
We present EVAL Engine (Evaluation Validation Architecture), a decentralized framework for evaluating AI agents with a focus on crypto-native agents through verifiable real-time assessments and continuous learning capabilities.
Our system utilizes Chromias gas-free relational blockchain architecture to enable transparent, immutable, and cost-effective evaluation of AI agent performance. The system incorporates multiple LLM-as-a-judge[1] and social engagement metrics for continuous reinforcement learning via feedback loop and reward system.
We demonstrate EVAL Engine can achieve efficient, secure evaluations while adapting to evolving performance standards through engagement-driven feedback loops.
We also present a comprehensive roadmap for the development of EVAL Engine, including API development, data preparation, model development, and model deployment.