Building an AI Email Triage System That Saves 4 Hours Per Week

Every knowledge worker spends 2-4 hours daily processing email. Most of that time is spent on classification, not composition. Here's how I built an AI-powered email triage system using the Claude API that cuts email processing time by 70%. The Architecture The system has three layers: Ingestion — IMAP polling fetches new emails every 60 seconds Classification — Claude API categorizes each email into action buckets Response Drafting — Auto-generates draft replies for routine messages Inbox → IMAP Fetch → Claude Classification → Action Router ├── urgent → Slack notification ├── routine → Auto-draft reply ├── newsletter → Archive + extract key points └── spam → Delete Step 1: Email Ingestion with IMAP We start with a simple IMAP poller that fetches unprocessed emails: import imaplib import email from email.header import decode_header from dataclasses import dataclass from typing import Optional import html2text @dataclass class EmailMessage : uid : str sender : str subject : str body : s