Operations automation

Automate Email Categorization and Routing

AI reads every incoming email, categorizes it by type and urgency, and routes it to the right person. Your shared inbox stays at zero.

Time savings

Task	Manual	Automated
Reading and categorizing emails	3-5 min/email	5 sec/email
Forwarding to correct department	2 min/email	Instant
Priority flagging	1 min/email	Instant
Response drafting for common queries	10 min/email	30 sec/email

Receive email
Automated

New email arrives at the shared inbox (info@, support@, sales@, etc.).
Analyze content
Automated

AI reads the email, identifies the intent, language, urgency, and relevant entities.
Categorize and tag
Automated

Apply labels: inquiry type (sales, support, billing, partnership), priority, and language.
Route to team
Automated

Forward to the correct team member or department channel with a context summary.
Team member responds
Human

The assigned person reviews the AI summary and responds to the email.

AI reads email content and classifies by type: sales inquiry, support request, billing question, partnership, spam.

Detect urgency from language cues, sender history, and keywords. High-priority emails get instant Slack alerts.

Forward to the right person or team based on category, language, and availability.

For common queries, the agent drafts a response for the team member to review and send.

Identify Arabic and English emails and route to team members with matching language skills.

Track email volume, response times, and category distribution to improve team capacity planning.

Does it work with Gmail and Outlook?

Yes. It connects to Gmail, Google Workspace, and Microsoft 365 inboxes via API.

Can it handle Arabic emails?

Yes. The agent processes Arabic, English, and bilingual emails, routing based on content language when needed.

What about attachments?

The agent analyzes attachment types and names for better categorization. For example, an email with an invoice PDF attached is tagged as billing.

How accurate is the categorization?

Typically 90-95% accurate after initial configuration. Misclassified emails are used to improve the model over time.

Set up automated email categorization for your team.