Zapier works until it doesn't. The moment a law firm tries to automate complex arrays or strict JSON schemas, Zapier hits a wall.
Most law firm automation breaks down for one reason: Zapier was built for marketers, not engineers. An attorney maps a Typeform payload with multiple dynamic questions into a strict MyCase custom field architecture and Zapier chokes. This is exactly the kind of issue that CRM API workflow overhaul addresses.
The Zapier limitations
Zapier operates on linear, 1-to-1 steps. You need to iterate over an array of 5 defendants and create 5 separate contacts in Clio before attaching them to a single Matter? Zapier forces you into complex, nested "Looper" zaps that are impossible to debug and burn through task execution limits fast. If you're experiencing these issues, our AI Workflow Repair Intake can help diagnose the problem.
The real problem: Zapier's Looper zaps look simple in the builder. They silently fail at scale, and you spend hours tracing which iteration broke and why. For a detailed comparison of automation platforms, see Zapier vs Make vs N8n for CRM automation.
The Make.com architecture
Make.com is an autonomous system router. Complex iteration, array aggregation, and strict error handling all work natively. No hacks required.
Here's how Make.com handles a 429 Rate Limit error when syncing documents to Google Drive:
[
{
"module": "Error Handler",
"directive": "Break",
"retries": 3,
"interval": 60000,
"action": "Store incomplete executions"
}
]Instead of dropping the payload and losing a client document, Make.com pauses the execution thread, waits 60 seconds, and retries. That's how you build resilient operations. You can see real examples of this approach in our production case studies.
Ready to migrate off Zapier? Download the Blueprint or start the AI Workflow Repair Intake.