EVM Restaking Risk Model Development

Continuous monitoring of validator performance and network conditions to predict and quantify slashing probability. We deliver actionable risk scores that inform delegation strategies and protect your staked assets.

Dynamic analysis of rewards across EigenLayer, Babylon, and other restaking protocols. Our models identify optimal allocation strategies to balance risk-adjusted returns, not just raw APY.

Comprehensive analysis of liquid staking token (LST/LRT) de-pegging risks, withdrawal queue liquidity, and protocol insolvency scenarios. Ensures your restaking positions remain solvent under stress.

Tailor risk thresholds, validator whitelists, and alerting rules to match your protocol's specific risk appetite. Integrates directly with your smart contracts or off-chain governance.

Critical risk calculation modules are formally verified using tools like Certora and Halmos. Provides mathematical guarantees against logic errors in your risk engine's most sensitive functions.

Generate detailed, on-chain attestable reports for risk exposure, historical performance, and compliance. Provides transparency for stakeholders, auditors, and governance participants.

Receive a real-time dashboard showing your protocol's exposure to specific slashing conditions, validator centralization, and liquidity risks across EigenLayer, Karak, and other AVS networks.

Deploy configurable alert triggers for critical risk thresholds. Our models integrate with your ops stack to enable automated responses, such as pausing deposits or rebalancing allocations.

Generate standardized, exportable risk reports that satisfy internal governance and external audit requirements. Document your risk framework with clear, verifiable data trails.

Identify underutilized or over-concentrated capital pools. Our models provide data-backed recommendations to optimize your restaking strategy for maximum yield per unit of risk.

We analyze the unique failure modes and slashing conditions of each underlying protocol (EigenLayer, Karak, Symbiotic) to build a granular, non-generic risk profile.

Development of probabilistic models using Monte Carlo simulations and historical on-chain data to quantify tail risks, correlation, and potential loss scenarios.

Secure, gas-optimized Solidity contracts that ingest our risk scores on-chain, enabling automated portfolio rebalancing and capital allocation decisions.

Our models are continuously validated against live mainnet data and backtested across historical stress events to ensure predictive accuracy and reliability.

Every component undergoes rigorous internal review and is built for external audit from day one, utilizing established patterns from OpenZeppelin and Solmate.

We handle the end-to-end integration of the risk model into your application's architecture, from off-chain APIs to on-chain oracles, ensuring seamless operation.