Multi-Agent Architecture for Halal Crypto Trading Compliance

Description and use

HalalCrypto built a multi-agent AI trading system to ensure Shariah compliance. Instead of a single model handling all tasks, four specialized agents—Screener, Signal, Risk, and Execution—operate independently. This separation ensures procedural compliance, prevents single-point failures, and provides an auditable trail for every trading decision.

Problem

Single-model AI trading systems risk 'prompt collisions' where the same model handles price analysis, halal compliance checks, and order execution, leading to probabilistic rather than procedural compliance and potential inclusion of haram assets.

Outcome

The multi-agent split ensures that the halal gate lives upstream of the trade gate on a different clock. It provides an auditable paper trail for every decision, allowing users to trace why specific trades were made or rejected, and prevents single-point-of-failure bugs like cache poisoning or implicit leverage.

Workflow

• Screener Agent runs a 4-gate halal filter (riba, gharar, maysir, haram-sector) every 24 hours to generate a permitted-coin list.
• Signal Agent generates entry hypotheses only on the permitted list, analyzing on-chain flow, momentum, and volatility.
• Risk Agent acts as a veto, checking position-size caps, exposure limits, and drawdown state; it kills candidates that breach rules.
• Execution Agent places spot-only orders on Binance via read+spot-only API keys, refusing any order that did not pass the previous three stages.
• Each agent writes inputs and outputs to a local audit log for traceability.

Evidence

The right architecture is multi-agent: a Screener that holds the halal gate, a Signal agent that generates entry hypotheses, a Risk agent that vetoes oversized positions, and an Execution agent that places only what survives.

Source

Fix: per-agent caches with hard TTLs, and a cold-start verification on every run.

Source