The core difference of Vanar Chain is not treating AI as a gimmick, but viewing the agent as a core user from the underlying architecture, removing the friction of agents going on-chain throughout the entire link, achieving 'long-term stable work, traceable and explainable, secure and controllable execution, and efficient settlement.'
Core Logic
Instead of letting agents adapt to the chain, let the chain actively adapt to the working methods of agents.
The core pain points of agents going on-chain: inability to remember, inability to articulate, instability in execution, difficulty in settlement, and limited distribution. Vanar's solution covers the entire process, breaking through one by one through modular design and native functionality.
Six core dimensions
1️⃣ Native adaptation of underlying architecture: AI-first rather than a last-minute addition
Vanar Stack modularization: five-layer architecture split into 'memory, inference, execution, settlement, industry adaptation', with independent and extensible modules to reduce calling complexity.
Full-chain decentralized storage: agent data processed on-chain, no centralized database required, ensuring trustworthiness and auditability.
Low-friction interaction: optimizing interfaces and Gas mechanisms, eliminating UI clicks and manual confirmations, allowing agents to directly invoke on-chain functions.
2️⃣ myNeutron: Solving the issue of 'not being memorable'
Semantic memory on-chain storage: work instructions, rules, and historical records are readable and queryable, forming a persistent context.
Reusable sharing: the historical memory of agents can be reused by other agents/systems to improve efficiency.
Verifiable and traceable: immutable on-chain, supporting context generation verification, ensuring auditability and interpretability.
3️⃣ Kayon: Solving the issue of 'not being clear'
Native on-chain inference: inference embedded in the protocol layer, no off-chain computation required, ensuring trusted decentralization.
Full traceability of decision chain: every step from instruction to result is recorded, forming a complete causal chain.
Layered interpretable output: presenting decision logic in natural language or visual causal graphs, meeting the needs of enterprises, audits, and developers.
4️⃣ Flows: Solving the issue of 'not being stable'
Multi-level behavioral guardrails: input validation, behavioral constraints, output filtering, preventing overreach or violations.
Refined permission management: principle of least privilege, whitelist, limits, and conditional triggers to ensure execution safety.
Abnormal warning and stop-loss: real-time monitoring, automatic pause of abnormal agents, log review to optimize operational rules.
5️⃣ Native payment/settlement: Solving the issue of 'difficult settlement'
Automated fee processing: agents can automatically pay Gas without human intervention.
Regulated settlement orchestration: automatically triggering the settlement process, achieving execution-reconciliation-settlement closed loop.
Multi-scenario settlement adaptation: supports games, supply chains, RWA, and other scenarios, where the agent works and settles immediately.
6️⃣ Cross-chain and ecosystem adaptation: Solving the issue of 'difficult distribution'
Cross-chain compatibility: EVM compatible, supports mainstream chain assets and data calls such as Base/Ethereum.
Complete toolchain: ADK, Vanar Hub, Academy, etc., support rapid development and deployment of agents.
Multi-industry scenario adaptation: games, supply chains, enterprise services, etc., allowing agents to be applied in more high-value scenarios.
Core Summary
Vanar Chain through myNeutron → Kayon → Flows → native settlement → cross-chain ecosystem, forming a full-link support system for agents:
Long-term stable work
Decisions are traceable and interpretable
Safe and controllable execution
Efficient settlement and distribution
Unlike other 'AI narrative projects', it is not a single-point optimization, but a full-link connectivity, removing fatal friction and supporting the next wave of 'automated workers' in Web3.
Core value: not about demonstrating coolness, but about agents creating real value every day.
