AI-Powered Inbox Triage
Classify, draft and route every incoming email so you only see what needs you.
/ quick answer
An LLM classifies every email into intent buckets (sales, support, admin, spam, personal), drafts a reply where safe, and applies labels + priority. Classify, draft and route every incoming email so you only see what needs you.
- 01Ingest new mail via Gmail API or a Make/Zapier trigger.
- 02Run a classifier prompt with a fixed enum of intents and a confidence score.
- 03For 'sales' and 'support': draft a reply grounded on your FAQ / RAG index; leave in Drafts, don't send.
- 04For 'admin': extract structured fields (invoice #, date, amount) and push to Notion.
- 05Apply Gmail labels + star; the human only reviews high-priority + drafts.
- Add a weekly 'inbox health' report with time saved and top intents.
- Route sales leads directly to CRM with enrichment.
/ frequently asked
What does the AI-Powered Inbox Triage workflow do?
An LLM classifies every email into intent buckets (sales, support, admin, spam, personal), drafts a reply where safe, and applies labels + priority.
What problem does AI-Powered Inbox Triage solve?
Founders and operators lose 1–2 hours/day to email that a system could handle. Filters aren't enough because intent is fuzzy.
How many steps does AI-Powered Inbox Triage take?
5 steps. It starts with ingest new mail via gmail api or a make/zapier trigger. and ends with apply gmail labels + star; the human only reviews high-priority + drafts..
How do I set up AI-Powered Inbox Triage step by step?
1) Ingest new mail via Gmail API or a Make/Zapier trigger. 2) Run a classifier prompt with a fixed enum of intents and a confidence score. 3) For 'sales' and 'support': draft a reply grounded on your FAQ / RAG index; leave in Drafts, don't send. 4) For 'admin': extract structured fields (invoice #, date, amount) and push to Notion. 5) Apply Gmail labels + star; the human only reviews high-priority + drafts.
Which tools does AI-Powered Inbox Triage need?
It uses ai-automation-operator-stack, no-code-automation-stack — each linked below with its own node.
/ continue exploring
Related concepts
The vocabulary this page depends on.
- →Structured Output
Forcing AI responses into predictable schemas that software can use.
- →Human-in-the-Loop
A control pattern where humans review high-risk AI decisions before execution.
- →Webhook
An HTTP callback that lets one system push data to another the moment an event happens.
- →PII Redaction
Stripping personally identifiable information before sending to a model.
Related workflows
Turn this into a repeatable process.
- →Telephony AI Voice Integration
Telephony AI Voice Integration is a workflow that connects AI voice agents with traditional phone systems to automate customer interactions, providing scalable and efficient support.
- →Dia: Automate Customer Support Research
This workflow utilizes Dia, an AI browser, to automate information gathering for complex customer support inquiries by searching across internal knowledge bases and external documentation. It reduces agent resolution time and improves consistency in responses.
- →Automated GitHub Issue Triage
Label, prioritize, and route incoming issues without a maintainer.
Related tool stacks
The tools that run it in production.
- →AI Automation Operator Stack
The default toolset for one operator running multiple AI-powered business workflows.
- →No-Code Automation Stack
The default toolset for an operator running business workflows without engineers.
- →Solo Founder Daily AI Stack
The 6-tool stack a solo founder actually uses every day — no fluff.
- →Community Manager AI Stack
Run an active community (Discord/Slack/Circle) with 1 CM + AI.
Related prompts
Reusable prompts for this job.
- →Lead Qualification Prompt
Score a lead against your ICP and explain the decision.
- →No-Code Automation Spec Writer
Turn a vague 'I want to automate X' into a buildable scenario spec for Make / n8n / Zapier.
- →Meeting to Actions Prompt
Extract decisions, owners, and dates from a meeting transcript.
- →Weekly Review Prompt
Automate the Friday review from calendar + tasks + notes.
Related use cases
How people apply it, and what came out.
- →Law Firm Automates Intake, Cuts Response Time 90%
Mid-sized firm deploys an AI intake agent for after-hours leads.
- →3-Person Agency Outproduces 15-Person Competitors
Boutique agency uses AI ops across delivery, sales, and reporting.
- →Coach Automates Onboarding, Doubles Client Count
Executive coach removes the 4h admin tax on every new client.
- →HR Team Screens 10x More Applicants With AI
50-person company handles 500 applicants/role instead of struggling with 50.
Comparisons & alternatives
Pick between the options.
- →Notion vs Airtable for AI Ops
Which one should run your AI workflow review queues and content calendar?
- →Airtable vs Notion vs Baserow
Relational data with different personalities.
- →Notion vs Obsidian vs Logseq
Cloud team wiki vs local plain-text knowledge base.