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Use Case:
Trading AI Agent
Key Challenges
Privacy of Strategy & PnL
The AI agent wants to hide specific trades, amounts, and overall profit/loss from other market participants (or even from the user’s peers).
Hidden Top-Ups & Withdrawals
Deposits into the strategy and withdrawals from it should not reveal amounts or user identities to the entire network.
AML Compliance
Some level of compliance or screening is necessary to prevent illicit fund flows. However, revealing full details to the public is undesirable.
Cross-Chain Movement
Some level of compliance or screening is necessary to prevent illicit fund flows. However, revealing full details to the public is undesirable.
Architecture Overview
Trading AI Agent
Deployed off-chain or on a server under the user’s control (or as a decentralized service).
Has private logic for identifying profitable trades (could be DeFi yield, arbitrage, or algorithmic trading).
Interfaces with INTMAX for user deposits, strategy position tracking, and bridging to external networks.
INTMAX Network
Stateless Rollup: Only commits a 5-byte Merkle root to Ethereum, so minimal on-chain data is revealed.
ZKP & Privacy:
Transactions (deposit, withdrawal) can remain private.
The strategy’s internal accounting of user assets is concealed from the public.
AML Screening (partial or integrated):
Could be enforced at bridging points or via a compliance layer that checks the origin of funds without revealing amounts to the public ledger.
External Trading Platforms
On Ethereum or other EVM-compatible networks (e.g., Arbitrum, Polygon) + Bitcoin
The AI agent interacts with DEX aggregators, DeFi protocols, or centralized exchanges (if any bridging/CEX API is available).
The agent performs trades or liquidity deployments with bridging from INTMAX.
Bridging Layer
The AI agent or aggregator contract handles the cross-chain transfer of user funds (in ETH, ERC20, etc.) for actual trading.
Native Bridge from INTMAX to Ethereum (and potentially onward to other L2s/networks using cross-chain bridges).
Summarized Flow
Trading AI Agent
User deposits into INTMAX (hidden amounts, minimal AML checks).
AI agent bridges portion of user funds to a chosen network for trading, hiding bridging details.
Trades & yields occur off-chain or on another chain, with no direct link to user’s identity.
Profits bridged back privately into INTMAX, updating the user’s balance with a ZK proof.
User withdraws from INTMAX to a public chain or keeps the funds privately in INTMAX, with optional AML check if needed.
Throughout the process:
The user’s identity, deposit size, trade details, and final PnL remain obscured from other users.
Compliance is maintained at bridging points with minimal public disclosure.
Only INTMAX’s Merkle root updates on Ethereum, so public chain watchers see almost no details about the user’s trading activity or performance.
Benefits
Full Strategy Privacy
Observers cannot front-run or copy the AI agent’s trades because amounts and timing are concealed.
Minimal On-Chain Footprint
Storing only a 5-byte Merkle root on Ethereum helps keep fees low, even with frequent bridging or high transaction volumes.
User Anonymity & AML Balance
The user’s personal or wallet details don’t appear publicly, but compliance checks can still be done discretely.
Scalability for Multiple Traders
The same architecture can handle many users or a pooled hedge fund model, with each user’s deposit and profit share tracked off-chain in INTMAX.
Flexibility to Use Any DeFi/CeFi
By bridging to external networks, the AI agent gains access to a broad spectrum of trading instruments, yield farms, and liquidity pools, while returning to INTMAX for private record-keeping.