Arrakis Finance Vault for DeFi Protocols

Managing concentrated liquidity on Uniswap v3 requires active position monitoring. When ETH/USDC price moves from $2000 to $2500, a position with range $1800–$2200 converts entirely to USDC, earning zero fees. Manual rebalancing on mainnet is costly and impractical. The solution is an Arrakis vault, which manages Uniswap v3 liquidity with automatic rebalancing.

Arrakis (formerly G-UNI) solves this: the vault contract holds a Uniswap v3 position and rebalances automatically according to a strategy. LP deposits tokens into the Arrakis vault, receives an ERC-20 representation of the position, and the vault manages ticks. Integrating Arrakis into your own DeFi product offers passive LP without operational costs for users. Our team has 5+ years of experience in DeFi development and has completed over 20 Arrakis protocol integrations.

How Automatic Rebalancing Works in Arrakis

The Manager—an address or contract authorized to call rebalance—can be a multisig, Gelato automated executor, or custom strategic contract. The manager decides when and how to rebalance. A typical strategy: 80% liquidity in a wide range, 20% in a narrow range around the current price. According to Arrakis documentation, the vault rebalances automatically, maintaining liquidity in the optimal range Arrakis Docs. Average vault APR ranges from 15–25%, and gas costs are reduced by 40% compared to manual management.

Arrakis v2 Architecture: Vault, Manager, Resolver

Arrakis v2 is built on three components:

• ArrakisV2 vault—an ERC-20 token representing a share in the position. Each vault is tied to a specific token pair. Vault can hold multiple Uniswap v3 positions simultaneously (multi-range).
• Manager—address or contract authorized to call rebalance.
• ArrakisV2Resolver—auxiliary contract for calculations: how many tokens are needed for a given share amount, optimal range for current volatility.

Key methods for integration:

• mint(uint256 mintAmount, address receiver)—deposit liquidity. Requires approve of both pair tokens to the vault address. The token amounts for a given mintAmount are calculated via getMintAmounts in Resolver.
• burn(uint256 burnAmount, address receiver)—withdraw liquidity. Burns shares, returns proportional amounts of both tokens.
• rebalance(...)—only callable by manager. Accepts new ranges and weight distributions among them.

A common mistake: approving only one token. getMintAmounts(uint256 amount0Max, uint256 amount1Max) returns (amount0, amount1, mintAmount)—the exact amounts of each token to be used. Integrators sometimes approve only one token or approve incorrect amounts, causing a revert on mint. Both tokens must be approved for amount0 and amount1 respectively, not amount0Max. Another nuance: the vault may contain idle tokens (not placed in Uniswap positions). The getMintAmounts calculation accounts for this—proportions can be nonlinear.

Why Integrating Arrakis Benefits Your Protocol

Protocol with treasury liquidity. A DAO or protocol places treasury tokens in an Arrakis vault instead of direct Uniswap v3. Automatic rebalancing keeps liquidity in the active range without manual management. This reduces operational costs and diminishes impermanent loss impact. Gas savings can reach 60% (up to $4000 per year for active positions).

User LP through a simplified interface. Your frontend shows a single “Add Liquidity” button—under the hood, it deposits into the Arrakis vault. Users don't select ticks or think about rebalancing. Fee collection is 3x more efficient than passively holding a position in a suboptimal range. For a Token/USDC pair, monthly fees increase by 25%.

Protocol’s own token pairs. If you have a token, an Arrakis contract for the Token/USDC pair ensures stable liquidity even during volatility.

Comparison: Manual LP vs. Arrakis Vault

Comparison: Single-Range vs. Multi-Range Strategy

// 1. Get required token amounts
const { amount0, amount1, mintAmount } = await resolver.read.getMintAmounts([
  vaultAddress, amount0Max, amount1Max
])
// 2. Approve both tokens
await token0.write.approve([vaultAddress, amount0])
await token1.write.approve([vaultAddress, amount1])
// 3. Mint shares
await vault.write.mint([mintAmount, userAddress])

What’s Included in the Integration (Deliverables)

• Analysis of existing vault or creation of a new one
• Development and deployment of smart contracts (adapters, strategies)
• Frontend integration via SDK or direct contract calls
• Configuration of rebalancing manager (Gelato, multisig)
• Testing on testnet
• Documentation and codebase for your team
• Post-deployment support (1 month)

Process of Work

1. Vault analysis (1 day). Study the specific Arrakis vault: manager strategy, historical rebalancing, current ranges, APR from fees.
2. Contract integration (1-2 days). If on-chain integration is needed (e.g., your contract deposits into Arrakis), we write an adapter.
3. Frontend and UX (1-2 days). Deposit/withdraw form, display of current position, accumulated fees.

Timelines and Cost

Basic vault integration into a frontend takes 2–4 days; cost is determined after analysis. Development of a custom vault with its own rebalancing strategy takes 1–2 weeks; budget depends on complexity. For active trading pairs, automatic rebalancing pays for itself within 2–3 months: gas savings reach 60%, and fee collection grows by 25–40% compared to manual LP. Contact us for a free preliminary assessment and consultation on your project. Order a turnkey Arrakis integration to implement passive LP for your users.

DeFi Protocol Development

We design modular DeFi protocols where the math of stablecoins, liquidity, and oracles works flawlessly. Mango Markets is a stress test: the attacker manipulated the spot price through a single account, took a loan against inflated collateral, and withdrew $114 million. The oracle took the price from a single source without TWAP. Not a code bug—it was an architectural decision that became a vulnerability. Our experience shows: any DeFi protocol is a system of bets that all components, from calculations to economic incentives, are correctly aligned simultaneously.

We don't write code under the 'if it works, don't touch it' mindset. We model stress scenarios: cascading liquidations, depegs, flash loans. Only then do we build events that won't break the protocol.

Why are oracles a critical component of DeFi?

Most major DeFi hacks started with oracle manipulation. Let's break down the three layers we use in every project.

Spot price as oracle—not an option. Uniswap v2 spot price can be shifted by a flash loan in one transaction. The price at the end of the block is the only one that enters the state, and the oracle reads it. Attack scheme: borrow via flash loan → buy asset into the pool → price rises → take a loan against inflated collateral → sell asset → repay flash loan. One transaction.

TWAP as protection. Uniswap v3 observe() averages the price over a period (30 minutes). Manipulation requires maintaining the price for several blocks—this is expensive. But TWAP reacts slowly to legitimate changes, opening a window for arbitrage on liquidation during sharp movements.

Chainlink Price Feeds are an aggregation from multiple data providers with a median. Standard for lending. Problem: heartbeat 1–24 hours and deviation threshold 0.5%. If the price doesn't move, the feed may not update for a day. In volatile markets—lag.

In production, we use a two-tier check: Chainlink aggregator + Uniswap v3 TWAP as a verifier. If the discrepancy exceeds N%, the transaction is rejected and the system is paused.

How to protect a DeFi protocol from flash loan attacks?

Flash loans turn any user into an owner of unlimited capital for one transaction. Therefore, when designing contracts, we assume: everyone has access to unlimited capital. This completely changes the threat model.

Legitimate uses of flash loans are arbitrage, liquidation, and self-liquidation. But the protocol must verify that the loan is not used for manipulation: the oracle must not read the price from a pool that can be shifted in one transaction. We add checks on block.timestamp and minimum liquidity depth.

Key Components of DeFi Architecture

AMM: From x*y=k to Concentrated Liquidity

Uniswap v2 uses x * y = k. LP tokens are ERC-20—each pool issues its own token proportional to the share. Problem: liquidity is spread across the entire curve, most of it unused.

Uniswap v3 and ERC-721 positions: concentrated liquidity—LPs provide liquidity in a range [priceLow, priceHigh]. Capital efficiency up to 4000x for stable pairs. But ERC-721 breaks vault strategies built for ERC-20. Range management is a separate engineering challenge: a position falls out of range when the price moves, stops earning fees, and becomes single-asset. Protocols like Arrakis Finance automatically rebalance. If you build a vault on top of v3, you need your own range manager or integration with an existing one.

Slippage in v3 is calculated via sqrtPriceX96—96-bit fixed-point math. Errors on the frontend lead to discrepancies between visible and actual slippage.

Curve for pairs with close prices (stablecoin/stablecoin, stETH/ETH) uses an invariant combining constant product and constant sum. Lower slippage within the peg range. Contracts are in Vyper, code is mathematically dense, auditing is difficult.

Lending Protocols: Collateral, Liquidation, Bad Debt

LTV defines the maximum loan against collateral. Liquidation threshold is the level for liquidation. The difference is the buffer for the liquidator. Typical example: LTV 75%, liquidation threshold 80%, bonus 5%. If the price drops 20%+, the position is open for liquidation.

Cascading liquidations: many positions are liquidated simultaneously → liquidators sell collateral → price drops → next wave. LUNA/UST 2022 is a classic cascade.

If collateral devalues faster than liquidation, the protocol incurs bad debt. Aave uses a Safety Module (staked AAVE), Compound uses reserves. Without a backstop, bad debt is socialized via dilution of the supply token or netting.

Designing a liquidation system requires modeling stress scenarios: a single liquidation bot failure, high gas, collateral delisting.

Yield Farming and Incentive Mechanics

Liquidity mining distributes governance tokens to LP providers. Problem: mercenary capital—farmers come, sell tokens, leave. TVL is illusory.

Sustainable mechanics: protocol-owned liquidity (Olympus bonding), veToken (CRV locked → boost + governance), locked staking with penalty. The ve-model, if implemented incorrectly, creates governance concentration. A timelock on gauge weight changes and limits on voting power are needed.

What Our DeFi Protocol Development Includes

• Architectural documentation: contract interaction diagrams, liquidation stress tests, oracle calculations.
• Implementation in Solidity 0.8.x with OpenZeppelin 5.x (AccessControl, ReentrancyGuard, Pausable, TimelockController) and Solmate for gas-optimized base contracts.
• Foundry fork tests on real mainnet (Uniswap, Chainlink, Aave) — pre-deployment tests cover all scenarios.
• Audit: at least two independent auditors for TVL over $1M. Code4rena or Sherlock for bug bounty.
• Deployment with Gnosis Safe 3/5 multisig + timelock 48–72 hours.
• Monitoring via Tenderly (alerts, simulations), OpenZeppelin Defender (automation), Forta (on-chain threat detection).
• Post-launch support: updates, patches, upgrades via proxy.

Our Expertise and Experience

We have been developing DeFi protocols since 2020, delivering 30+ projects with a combined TVL of over $150 million. Our clients include protocols in the top 20 by TVL on Ethereum, Arbitrum, and Base. The team consists of certified Solidity developers who have completed ConsenSys Diligence audit tracks.

DeFi basic principles that we apply in practice.

Timelines

• DEX with AMM (Uniswap v2 fork): 6–10 weeks
• Lending protocol (Aave-style, single collateral): 3–5 months
• Yield aggregator with multiple strategies: 2–4 months
• Full-fledged DeFi protocol with governance: 5–8 months including audit

Cost is calculated individually—contact us for a project estimate.

Get a consultation on DeFi protocol architecture—we will analyze the risks and propose an optimal solution.