Zapier
What is Zapier?
Zapier is a no-code automation platform that allows users to create workflows (called "zaps") that connect different applications and services. A zap is triggered by an action in one application and then initiates one or more subsequent actions across multiple applications.
In AI product development, Zapier can be used to orchestrate AI workflows—for example, triggering LLM calls when users submit input, aggregating responses, and delivering results via email or other services—all through a no-code interface.
How does Zapier work for AI workflows?
Zapier makes it easy to prototype and deploy simple AI workflows without writing code:
Trigger: An action in one application starts the workflow. For example, a student submitting an interview transcript through a course platform.
AI tasks: The zap can call LLM APIs (like Anthropic's API) to process the input, making multiple LLM calls if needed.
Aggregation and processing: Custom code steps within Zapier can combine responses from different LLM calls.
Delivery: The workflow can send results via email (using services like AWS SES) or route them to other applications.
This cross-application integration makes Zapier valuable for quickly connecting AI capabilities with existing tools and services.
What are Zapier's limitations for production AI products?
While Zapier works well for prototyping and simple automation, it has limitations for production AI products:
Error handling: When errors occur, Zapier can put automations on hold for up to eight hours. For time-sensitive AI applications where users expect immediate responses, this creates poor user experiences.
Reliability concerns: The delayed error handling means users may be left wondering where their results are, undermining confidence in the AI product.
These limitations often lead teams to migrate from Zapier to more robust orchestration solutions like AWS Step Functions as their AI products mature and scale.
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