Make vs Relevance AI

When to pick Make

• Your automations are deterministic and integration-heavy: route a form submission through enrichment, a CRM, Slack, and a drip sequence in one branching scenario.
• You want the lowest entry cost and a real free tier — Core is $9/mo and the free plan runs 1,000 operations across 2 scenarios with no expiry.
• You need the widest connector library: 3,000+ pre-built apps plus an HTTP/webhook module that reaches any REST API without a native integration.

When to pick Relevance AI

• You need agents that reason rather than follow fixed steps — qualifying leads, triaging tickets, or drafting outreach where each case needs judgment, not a preset branch.
• You operate in high-stakes or regulated workflows: human-in-the-loop gates, approval flows, and RBAC/audit logs make agent output reviewable before it acts.
• You want native multi-model flexibility — swap between Claude, GPT-4o, and Gemini with built-in cost comparison and BYOK, without rebuilding the agent.

Bottom line

Make and Relevance AI sit at different altitudes of “no-code.” Make is the stronger, cheaper choice for deterministic automation — thousands of connectors, branching logic, and a genuine free tier from $9/mo make it the default for wiring apps together. Relevance AI is purpose-built for autonomous agents that make decisions and handle exceptions, with human-in-the-loop governance and native Claude, GPT-4o, and Gemini support from $19/mo. Pick Make to move data between systems reliably; pick Relevance AI when the work requires an agent that reasons.