Most email-to-notes tools just dump everything into a pile. You forward content, and it becomes a note. That's it. Organization, categorization, and action are all on you.

Lolodex works differently. When you forward an email, AI analyzes the content and determines what you want to do with it. This automatic routing is called intent classification.

What is Email Intent Classification?

Key Concept

Email intent classification uses AI to analyze the subject and body of forwarded emails to determine what action you want: save as a note, ask a question, add a todo, or request research. This happens automatically, so your emails are processed intelligently without manual tagging or sorting.

The Problem It Solves

Traditional approach: All emails → unsorted notes pile → manual organization required

With intent classification: Emails → intelligent routing by purpose → automatic organization

Why This Matters

  • Questions get answered (not just stored)
  • Tasks get extracted (not lost in notes)
  • Notes get saved and organized (not piled)
  • Research gets triggered (when needed)

The Four Intent Types

1. Save Note (Default)

Trigger: Most forwarded content defaults here

Action: Creates a searchable note with full content, extracts key information, and links to related notes

Best for: Newsletters, reference emails, articles, meeting notes

Example

Forward a newsletter → Saved with subject as title, content searchable, auto-organized by source

2. Ask Question

Trigger: Email contains a question about your existing knowledge

Action: Searches your knowledge base, generates an answer, and replies via email

Best for: Retrieving information, synthesizing content from multiple notes

Example

"What did John say about the Q4 budget?" → AI searches notes, finds relevant content, sends answer via email

3. Add Todo

Trigger: Email contains clear action items or task requests

Action: Extracts tasks and creates linked todos in your task list

Best for: Emails with action items, meeting follow-ups, request emails

Example

Forward meeting notes with "Action items: 1. Call vendor, 2. Update proposal" → Two todos created, linked to source note

4. Research

Trigger: Email requests information not in your knowledge base

Action: Triggers web research, compiles findings, returns results via email, and saves to your knowledge base

Best for: Questions about external topics, competitive research, general information needs

Example

"Research: best practices for remote team onboarding" → AI researches topic, sends summary, saves findings

How the AI Classifies Intent

Natural Language Processing

The AI analyzes both subject line and email body, looking for:

  • Question markers: Question marks, interrogative words (what, when, how, why)
  • Action language: "Need to," "should," "will," deadlines, assignments
  • Research indicators: "Find out," "research," "what is," external information requests
  • Save signals: Forwarded content, "FYI," informational language

Confidence Scoring

  • High confidence: Routes immediately to detected intent
  • Low confidence: Defaults to "Save Note" (safest option)

Tips for Clear Intent Signals

For Questions

  • Start with question words: "What," "When," "How"
  • Use question marks
  • Example subject: "Q: What was the budget decision?"

For Todos

  • Use action words: "TODO," "Action items," "Tasks"
  • Example subject: "FW: Action items from meeting"

For Research

  • Use "Research:" prefix
  • Ask about external topics not in your notes
  • Example: "Research: Competitors in enterprise AI space"

When Classification Goes Wrong

Manual Override

If an email is misclassified, you can manually recategorize in your dashboard. The system learns from these corrections over time.

Edge Cases

Some content is genuinely ambiguous. A newsletter with a question in it will save as a note (not trigger Q&A) because the primary intent is archival. This is expected behavior.

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Intent classification transforms email from a dump-everything system into an intelligent router. Your emails are processed according to their purpose, not just stored. The result is a knowledge base that actively works for you.