Make vs Relevance AI
A direct comparison of two productivity & workflow tools — what each does well, where each falls short, and which is the better fit depending on your situation.
Make
Make
Visual workflow automation for complex processes
Relevance AI
Relevance AI
Build and deploy custom AI agents for your business
Feature Comparison
| Make | Relevance AI | |
|---|---|---|
| Company | Make | Relevance AI |
| Founded | 2012 | 2020 |
| Pricing | Free tier · Core $9/mo · Pro $16/mo · Teams $29/mo | Free tier · Team from $19/mo · Business custom |
| Key features |
|
|
Make
Pros
- +Visual canvas makes complex multi-branch workflow logic comprehensible
- +Handles data transformation and conditional logic that simpler tools can't
- +More affordable than Zapier for equivalent operation counts
- +Excellent error handling and retry logic for production-grade automation
- +1,000+ app integrations with detailed control over request/response handling
Cons
- −Steeper learning curve than Zapier — not instant for first-time automation builders
- −Visual complexity of large workflows can become hard to navigate
- −Less polished UI and documentation than Zapier
- −AI assistance for workflow building less advanced than Zapier's AI features
Relevance AI
Pros
- +Custom agent builder handles specific business workflows with consistent output
- +Agents can use tools: web search, code execution, API calls, data lookup
- +Teams of agents can collaborate on complex multi-step research or production tasks
- +More powerful and flexible than off-the-shelf automation for custom requirements
- +Agents deployable as webhooks, on schedules, or embedded in other tools
Cons
- −More configuration required than simpler tools like Lindy
- −Requires understanding of agent architecture to build effective workflows
- −Debugging agent behaviour requires more technical patience
- −Best for teams with a specific workflow problem to solve, not general AI assistance
Make is best for
- Ops teams needing automation with complex conditional logic and data transformation
- Teams who find Zapier too limiting for multi-branch or non-linear workflows
- Agencies building and maintaining automations for multiple clients cost-effectively
Relevance AI is best for
- Teams building repeatable custom workflows like lead enrichment or content pipelines
- Operations leads who need AI agents with consistent, predictable output
- Companies with specific processes to automate that off-the-shelf tools don't cover well
Bottom line
Make: The right choice for operations teams that have outgrown Zapier's simplicity and need automation with complex conditional logic, data transformation, and robust error handling. The steeper learning curve is worth it when the workflow genuinely requires the flexibility Make provides, and the per-operation pricing is more cost-effective at high volumes.
Relevance AI: The right choice for teams with a specific, high-volume business process to automate that requires custom logic and consistent, auditable output at scale. If you are building a lead enrichment pipeline, a competitive monitoring workflow, or any process that needs to run reliably thousands of times with predictable results, Relevance AI's structured agent platform is built for that.