Zapier AI

Build AI-powered workflows that connect 7,000+ apps without writing code.

4.5 (4)

レビュー: Daniel Nikulshyn·更新 2026年5月

Productivity No-Code AI Agents Workflow Automation LLM Chatbots Integrations

概要

Zapier AI extends Zapier's long-running automation platform with generative AI features that help users describe, build, and refine workflows in plain English. It can suggest multi-step Zaps, draft logic, and embed large language model actions directly into automations across thousands of supported applications. Beyond classic triggers and actions, Zapier AI introduces agents and chatbots that can reason over data, call connected tools, and take action on a user's behalf. This makes it useful for teams that want to automate routine work like lead routing, content generation, ticket triage, or internal reporting without committing to custom development.

主な機能

Conversational Zap builder
AI actions for OpenAI, Anthropic and others
Custom AI agents with tool access
Built-in chatbot creation
Multi-step workflows with branching
Tables and Interfaces for data and UI

ユースケース

Automate Lead Routing Across Tools

Use natural language to build multi-step Zaps that capture leads, enrich data with AI, and route them to the right CRM, Slack channel, or sales rep.

AI-Powered Ticket Triage

Deploy an AI agent that reads incoming support tickets, classifies urgency, drafts responses with an LLM, and assigns them to the correct queue.

Generate Content in Workflows

Embed OpenAI or Anthropic actions into Zaps to draft marketing copy, social posts, or email replies as part of an automated publishing pipeline.

Internal Reporting Chatbot

Build a no-code chatbot with tool access that pulls data from connected apps and Zapier Tables to answer team questions and summarize reports on demand.

メリット & デメリット

メリット

Natural language Zap creation
Massive app ecosystem (7,000+)
No-code AI agents and chatbots
Integrates with major LLM providers
Reusable templates and shared workflows

デメリット

Task-based pricing can scale quickly
Advanced logic still requires learning curve
AI suggestions may need manual cleanup
Complex agents can be hard to debug

レビュー

4.5

4件の評価の平均。

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Frank Müller

Does the job

Pretty happy overall. Tables and Interfaces for data and UI just works and reusable templates and shared workflows. Complex agents can be hard to debug can be annoying, but no dealbreakers — I'd recommend it to a friend without hesitating.

Marcus Bell

Years in this space

I've evaluated a lot of these over the years. What stands out here is multi-step workflows with branching — handled better than most — and integrates with major LLM providers. Worth the time if this is your use case.

Camille Laurent

Does the job

Pretty happy overall. Built-in chatbot creation just works and reusable templates and shared workflows. AI suggestions may need manual cleanup can be annoying, but no dealbreakers — I'd recommend it to a friend without hesitating.

Beatriz Costa

Solid for our team

We rolled this out across the team last quarter and natural language Zap creation. Tables and Interfaces for data and UI fits neatly into how we already work, and tables and Interfaces for data and UI removed a step we used to do by hand. but it has held up under daily use.