Use Cases

This section highlights specific and recurring use cases where the Flodea Privacy Layer provides significant functional and security advantages. These use cases reflect real operational needs across Web3 infrastructure, DeFi, governance, and privacy-first AI.

Each use case is directly powered by one or more modules in the Flodea Privacy Layer and demonstrates the impact of privacy-by-default agent infrastructure.

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1. Anonymous DAO Voting

Problem DAO participants often face privacy concerns when voting, especially in politically sensitive or high-value decisions.

Solution with Flodea The Privacy Layer enables agents to vote using zkVoting and stealth wallet identities. This ensures that voting decisions remain anonymous while still being verifiable.

Modules Used

• zk Access Control

• Stealth Wallet

• Encrypted Storage (for vote history)

2. Private DeFi Arbitrage Agent

Problem Traditional arbitrage bots can be tracked and frontrun by others monitoring mempools or on-chain patterns.

Solution with Flodea The agent can route through private networking (Tor or DeVPN) and use a stealth wallet to hide transaction origins and asset flows.

Modules Used

• Private Networking (Tor, DeVPN)

• Stealth Wallet

• Encrypted File System

3. Hidden Airdrop Hunter Agent

Problem Publicly operating airdrop bots can expose wallet identity and reduce eligibility or create sybil attack risk.

Solution with Flodea The agent can operate using wallet rotation, encrypted storage, and anonymous access to campaigns. Airdrop tasks are triggered without leaving a detectable trail.

Modules Used

• Encrypted Storage

• Wallet Obfuscation

• Private Routing

4. RWA Contract Executor with Confidential Logic

Problem Some real-world asset contracts involve sensitive legal or financial logic that should not be exposed to the public chain.

Solution with Flodea The agent can run the decision logic in an encrypted local environment, validate triggers with zk proofs, and initiate contract actions anonymously.

Modules Used

• Encrypted Storage

• zk Access Control

• Private Networking

5. Confidential Research or Document Analysis Agent

Problem AI agents working with proprietary or private data need to ensure that no raw data is exposed during inference or task processing.

Solution with Flodea Using encrypted storage and isolated runtime, the agent can perform confidential inference, summarization, or document classification tasks.

Modules Used

• Encrypted File System

• Local AI Runtime

• Optional Network Isolation