Relay.app vs Stripe Radar

Human-in-the-loop design is a first-class feature, not an afterthought — you can drop approval gates and manual review steps directly into workflows, which is exactly what teams need for processes involving customer communication or high-stakes decisions.

The chat-first builder lets you describe an automation in plain language and have Relay.app assemble it, meaningfully lowering the barrier for non-technical users compared to configuration-heavy alternatives.

Model-agnostic AI support means you can route steps through GPT, Claude, or Gemini rather than being tied to a single provider, giving flexibility as model quality and pricing shift.

Fine-grained access controls over what each automation can see and do make it more defensible for workflows that touch sensitive business or customer data.

Runs natively inside Stripe's payment flow, so merchants already on Stripe get fraud scoring with virtually no additional integration work.

Machine learning models are trained on transaction data across millions of Stripe businesses, giving it a network-wide view of fraud patterns that a single merchant can't replicate alone.

Uses rich contextual signals — billing and shipping addresses, customer history, and buyer behavior captured in checkout — to score risk without adding friction for legitimate customers.

The advanced Fraud Teams tier gives risk analysts real control: custom rule-building, allow/block lists, manual review queues, and detailed fraud analytics.