Vanar's technology stack is genuinely tailored for AI from the ground up, not a patchwork of AI modules added later. It features a five-layer architecture where each layer is intricately connected, focusing on the storage, inference, and automation of AI on the blockchain, enabling applications not only to run but also to understand.
First, the underlying Vanar Chain: This is the core blockchain layer, EVM compatible, with high performance and low fees (around $0.0005 per transaction), achieving a daily transaction volume of over 150,000, with more than 26 million transactions across the network. The key is that it optimizes AI workloads—featuring built-in vector storage, similarity search, and distributed computing, capable of running AI models in sub-second speeds, and supports semantic transactions (contracts that understand context). It essentially lays a solid foundation for the entire stack.
Next, Neutron: This is the semantic memory layer, the most hardcore part. Traditional chains are expensive and cumbersome for data storage, while Neutron uses an AI compression engine to reduce documents, images, emails, and other miscellaneous items into ultra-small “Seeds” (knowledge seeds), achieving a compression ratio of up to 500 times (25MB down to 50KB). Seeds are not only small but also carry semantic embeddings and cryptographic proofs, verifiable, queryable, and executable across the entire chain. In simple terms, it transforms dead data into living AI memory, allowing agents or applications to directly ask questions, extract insights, and even trigger contracts. Privacy is also secure, with client-side encryption where only the owner has the key.
Further up is Kayon: The AI inference brain. It directly consumes Neutron's Seeds for context inference, natural language queries (it answers complex questions in English), and compliance automation (supporting rules from over 47 countries for automatic reporting). For example, asking, "Which wallets bridged over $1 million to L2 last week?" it provides an answer instantly along with an audit trail. Cross-chain and enterprise system integration is smooth, operating without oracles, running across the entire chain, with verifiable outputs.
Then there’s Axon: The intelligent automation layer, currently being promoted, focusing on Agentic workflows, enabling on-chain applications to self-optimize and automatically execute complex processes.
At the top is Flows: Industry application templates, quickly deploying in scenarios like gaming, PayFi, and RWA.
Overall, Vanar does not engage in the superficial; it is natively built across the entire chain from storage to inference, addressing the pain points of AI agents needing real memory and decision-making. Institutions engaging in RWA, PayFi, or AI gaming can stack these components, leading to explosive efficiency. Personally, I believe this is how an AI chain should look.
