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Automations are how ShingleAI turns your inbox from a task list into a system that works for you. Instead of manually processing every message, you define rules in plain English and let AI handle the routine work.

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What Are Automations?

An automation is a workflow that runs when something happens in ShingleAI. Every automation has three parts:
  1. Trigger — the event that starts the automation (e.g., a new email arrives)
  2. Instructions — what you want the AI to do, written in natural language
  3. Permissions — what actions the automation is allowed to take
What makes ShingleAI automations different from traditional “if this, then that” rules is the AI layer. Instead of rigid conditions and fixed responses, you describe what you want in plain English and the AI interprets each situation individually.

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How Automations Work

When an event occurs — say a new email arrives — ShingleAI checks if any active automations match that trigger. If so, the AI reads the incoming content, evaluates your instructions, and takes action. Here’s the flow:
  1. Event occurs — A new email, contact creation, or other trigger event happens
  2. Trigger matches — ShingleAI identifies automations listening for this event
  3. AI processes — The AI reads the content and interprets your instructions
  4. Action taken — The AI performs the appropriate action (reply, create contact, etc.)
  5. Result logged — The execution is recorded so you can review what happened
The AI doesn’t follow a decision tree — it understands context. An instruction like “if this looks like a support request, send an acknowledgment” works because the AI can evaluate whether an email is a support request, even if the sender doesn’t use the word “support.”

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The Power of Natural Language Instructions

Traditional automation tools require you to define exact conditions: “if subject contains ‘help’ OR subject contains ‘support’ OR subject contains ‘issue’…” This is brittle and misses edge cases. ShingleAI automations use AI instructions instead: 
When a new email arrives:
1. If it looks like a support request, send a friendly acknowledgment
2. If it's a sales inquiry, tag the contact as "Lead"
3. If it's a newsletter or automated notification, do nothing
The AI handles the ambiguity. It understands that “My login isn’t working” is a support request even though it doesn’t contain the word “support.”

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What Can Automations Do?

Automations can take a range of actions depending on their permissions:
  • Send replies — Compose and send email responses
  • Create and update contacts — Add new contacts or update existing ones
  • Manage messages — Archive, label, or categorize incoming messages
  • Send notifications — Alert team members about important messages
  • Create tasks — Generate follow-up tasks from incoming requests

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Automation Lifecycle

Automations have a lifecycle with different states:
StatusMeaning
ActiveRunning and processing events as they occur
PausedTemporarily disabled — can be resumed at any time
CompletedFinished after reaching an execution limit
ExpiredPast its configured expiration date
You can pause an automation at any time without losing its configuration. This is useful when you want to temporarily stop processing while you refine your instructions.

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Automations and Permissions

Automations run with the permissions that were set when they were created. They cannot perform actions beyond their granted permissions. This means:
  • An automation with read-only message access can analyze emails but not reply
  • An automation without contact permissions cannot create or modify contacts
  • Permissions are checked on every execution, not just at creation time
This design ensures automations stay within the boundaries you define, even as the AI interprets instructions flexibly.

Create your first automation

Step-by-step guide to building an automation

Tutorial: Handle support emails

Build a working AI-powered support workflow from scratch