Roadmap
Development phases, milestones, and future direction for Aquarius.
Aquarius development follows a phased approach, expanding from a single-protocol proof of concept to a multi-chain, multi-protocol protection infrastructure.
Focus: Deepen Aave coverage and prove the architecture.
| Milestone | Description | Status |
|---|---|---|
| Aave V3 full integration | Complete risk monitoring, mitigation, and validation | Done |
| BufferVault deployment | Pooled capital protection with share mechanics | Done |
| Dual-path mitigation | Non-custodial and vault-backed pathways | Done |
| 11-stage validation | End-to-end architecture validation pipeline | Done |
| AI Risk Agent | Deterministic + LLM-augmented decision engine | Done |
| Tenderly simulation | Fork-based testing and dry-run validation | Done |
| Uniswap LP risk model | Impermanent loss monitoring and LP position risk scoring | In Progress |
| Liquidation prediction | ML-assisted health factor forecasting | In Progress |
Focus: Multi-chain and multi-protocol expansion.
| Milestone | Description |
|---|---|
| Multi-chain risk propagation | CCIP-based cross-chain risk broadcasting with automated response |
| Cross-protocol monitoring | Detect correlated risk across Aave, Uniswap, Compound, and Lido positions |
| Institutional dashboard | Dedicated interface for fund managers and treasury operators |
| Protocol SDK | Enable any protocol to integrate Aquarius risk intelligence natively |
| Compound V3 adapter | Risk monitoring and mitigation for Compound lending positions |
| Lido staking risk | Validator exposure, slashing risk, and withdrawal delay monitoring |
| Advanced stress testing | Multi-asset correlation-aware scenario simulation |
Focus: Become the standard protection layer for on-chain finance.
| Milestone | Description |
|---|---|
| TradFi-grade capital protection | Institutional-quality risk management meeting regulatory expectations |
| RWA monitoring | Real World Asset risk assessment and protection |
| Compliance-aware escalation | Jurisdiction-sensitive risk response for regulated entities |
| Formal verification | Mathematical proofs for critical contract logic |
| Decentralized governance | Community-driven protocol parameters and upgrade proposals |
| Insurance integration | Connect vault protection with on-chain insurance protocols |
The AQUA token serves three functions within the Aquarius ecosystem:
| Function | Description |
|---|---|
| Governance | Vote on protocol parameters, risk thresholds, and upgrade proposals |
| Staking | Stake AQUA to participate in risk validation and earn protocol fees |
| Incentives | Earn AQUA for providing vault liquidity and participating in governance |
Vault tokens represent participation in the BufferVault:
| Property | Description |
|---|---|
| Claims | Proportional claim on underlying vault assets |
| Yield-bearing | Value increases as vault earns protection fees |
| Mitigation backing | Represents contribution to the collective protection pool |
| Composable | Future: ERC-20 wrapping for DeFi composability |
Transparency about current limitations demonstrates engineering maturity:
| Limitation | Context | Mitigation |
|---|---|---|
| Aave-first | Only Aave V3 is fully integrated | Protocol adapter architecture enables straightforward expansion |
| Simulation coverage | Not all edge cases are covered | Expanding stress test scenarios continuously |
| No formal audits | Smart contracts not yet audited | 11-stage validation pipeline provides interim assurance; formal audit planned |
| Cross-chain observe-only | CCIP integration is informational only | Mitigation execution across chains is on the roadmap |
| Single LLM provider | Groq with llama-3.3-70b-versatile | LLM layer is advisory and non-blocking; provider-agnostic design allows switching |
Active research areas that will inform future development:
Replace linear HF projection with machine learning models trained on historical liquidation data. Target: improve prediction accuracy from ~85% to ~95% confidence at 100-block horizons.
Current stress tests treat assets independently. Future models will capture correlations — e.g., ETH and stETH moving together during a depegging event, or broad market crashes affecting all collateral simultaneously.
Research optimal reserve ratios and injection strategies to maximize capital efficiency while maintaining sufficient liquidity for mitigation events. Includes game-theoretic analysis of depositor incentives.
Apply formal methods to critical smart contract logic: