# Euler Growth Phases

#### **PHASE 1 – Core Infrastructure Deployment**

**Euler SVM Chain**\
Launch a Solana Virtual Machine–powered execution layer purpose-built for AI-native workloads. This chain supports scalable, low-latency environments for deploying autonomous, multi-agent AI systems with parallelized smart contracts and seamless state synchronization.

**zkML & TEE Integration**\
Incorporate zero-knowledge machine learning (zkML) and trusted execution environments (TEE) to ensure data privacy, secure model inference, and tamper-proof agent operations—critical for sensitive AI applications running on open networks.

**Euler Benchmark**\
Deploy an on-chain performance evaluation framework for AI models and agents. It standardizes benchmarking metrics, verifies compute outputs, and introduces a transparent scoring mechanism to enforce quality and accountability in model performance.

**Euler Orchestrator**\
Establish a decentralized coordination layer to manage multi-agent interactions, inference routing, and automated task assignment. The orchestrator enables real-time interoperability between AI agents and smart contracts through composable logic flows.



#### **PHASE 2 – Tokenomics & Governance Layer**

**$EULER Token**\
Introduce a native utility token that powers the entire Euler ecosystem. $EULER will be used for incentivizing compute contributions, model deployment, orchestration fees, and platform governance.

**Superalignment DAO**\
Form a decentralized autonomous organization tasked with protocol upgrades, fund allocation, and alignment of ecosystem incentives. Governance will prioritize the long-term integrity and safety of AI deployment onchain.



#### **PHASE 3 – Ecosystem Growth & Integration**

**Strategic Partnerships**\
Forge collaborations with AI labs, web3-native projects, research institutions, and DeFi protocols to extend the Euler stack across use cases ranging from decentralized AI agents to finance, gaming, and autonomous data networks.

**Platform Scaling**\
Advance the scalability and throughput of the Euler stack to support millions of real-time AI interactions. This includes state sharding, optimized inference caching, and cross-chain operability to handle high-frequency, AI-driven workflows.
