Shared Inbox Overload? AI Email Triage Sorts and Routes info@ and sales@

Your shared inbox is where opportunities and problems arrive together. A quote request sits between a supplier invoice and a newsletter. A customer complaint waits behind thirty cold pitches. Whoever checks info@ first decides what happens, and on a busy day, some messages are simply missed.

The cost shows up in slow replies, lost leads and frustrated customers who email twice. It also shows up in your team's day. Skilled people spend their mornings reading, forwarding and copying details into the CRM instead of doing the work those emails are about.

What this automation does

AI email triage reads every new message in a shared mailbox such as info@, sales@ or support@ and handles the sorting work. For each email it can:

• Classify the message: sales enquiry, support request, billing, supplier, job application, spam or other.
• Summarise it in one or two lines, so the reader knows what is needed before opening it.
• Extract key data such as company name, order number, product, deadline or requested quantity.
• Draft a reply for a person to review, edit and send.
• Route the message to the right person, team or queue.
• Remind the owner when an important email has not been answered in time.

It works with Gmail and Google Workspace and with Microsoft 365 and Outlook.

What a triaged email looks like

Picture a message arriving at sales@ from a distributor. Within a minute it carries a "Quote request" label and a high-priority flag. A one-line summary sits at the top: 200 units of a named product, delivery needed before month end. The company and contact are already in the CRM as a new deal, assigned to the right account manager. A draft reply asking two clarifying questions waits in the drafts folder. If nobody sends it by the afternoon, the account manager gets a nudge.

How it works, step by step

1. Watch the mailbox. The workflow connects to the shared mailbox through the Gmail or Microsoft Graph API and picks up new messages as they arrive.
2. Apply simple rules first. Known senders, auto-replies and obvious newsletters are handled by ordinary filters. This keeps cost down and leaves the AI for messages that need judgement.
3. Classify and summarise. The AI model reads the message and returns a category, a short summary, an urgency level and a confidence score in a fixed format.
4. Extract the details. Fields you care about are pulled out and checked. A missing order number or an unknown customer is flagged rather than guessed.
5. Route. Based on the category and your routing table, the email is labelled, moved or assigned. It can also create a CRM lead or a helpdesk ticket with the extracted data attached.
6. Draft a reply. For common requests, the AI writes a draft using your templates and, where useful, facts from your own documents. The draft waits in the mailbox for approval.
7. Send to review when unsure. Messages below the confidence threshold go to a review folder with the AI's suggestion attached.
8. Chase. If a high-priority email has no reply after the time you set, the owner gets a reminder in Slack, Teams or Telegram.

Tools we use

• Self-hosted n8n to run the workflow on infrastructure you control.
• Gmail or Microsoft 365, through their official APIs and an account with the right permissions.
• An LLM: OpenAI, Anthropic Claude, or a private open-source model for sensitive mailboxes.
• Your CRM or helpdesk, such as HubSpot, Pipedrive, Salesforce, Zendesk or Freshdesk.
• Slack, Teams or Telegram for reminders and escalation.

Check the current pricing and API terms of each tool before you start, as both change.

What you need to get started

• The list of mailboxes in scope and an admin who can grant API access.
• Your categories and who owns each one. A one-page routing table is enough.
• A sample of real past emails, with sensitive content removed if needed, to test classification.
• Your standard replies and any documents the drafts should draw on, such as pricing sheets or policies.
• Agreed response times for each category, so reminders mean something.

Typical scope and timeline

As an estimate, a first version usually takes 1 to 3 weeks of work. One mailbox with classification, routing and reminders sits at the short end. Several mailboxes, CRM and helpdesk integration, and reply drafts grounded in your documents take longer.

We normally run the first version in "shadow mode" for a short period. The AI labels and drafts, but people still route by hand and compare. Once the team is happy with the accuracy, routing is switched on.

Risks and how we handle them

Wrong classification or bad drafts

No model gets every email right. We use confidence thresholds, a review folder for uncertain messages, and human approval for every customer reply. Misrouted emails can be corrected with one click, and those corrections feed into better instructions.

Privacy and sensitive content

Emails contain personal data. We send only what the model needs and avoid storing message bodies in logs. Attachments stay out of the AI step unless they are needed. For mailboxes with health, legal or financial content, a private model can run in your own environment. Our post on private RAG for regulated data explains the options.

Failures and missed emails

If the workflow stops, emails must not disappear. Messages stay in the mailbox until they are processed. Failed steps are retried and logged, and a technical contact is alerted if the queue backs up. Nothing is deleted by the automation.

When not to build this

• Low volume. If one person can comfortably read the shared inbox in a few minutes a day, a few mail rules are enough.
• Your helpdesk already does it. Many helpdesks now include AI tagging and reply suggestions. If most of your email already flows into one, try those features first.
• No clear owners. Routing only helps if each category has someone who will act. Fix ownership first.
• You want fully automatic replies to complex questions. We would advise against it. The risk of a confident wrong answer to a customer is usually not worth it.

How UnlockLive can help

We build inbox triage as part of our AI Workflow Automation service. If you want drafts grounded in your own documents and policies, our RAG development service covers the knowledge side. The same approach powers our AI support ticket triage workflow.

Inbox triage often connects to other automations. Sales emails can trigger automated lead follow-up. Invoices arriving at accounts@ can go straight into AI invoice processing. Contracts and forms can feed AI document data extraction.

For a reference point, our Branify customer service case study describes a larger AI system. There, 70% of tickets were resolved without a human, and average handle time fell by 45%. Inbox triage is a smaller, safer first step in the same direction.

Want to know what your shared inbox could look like? Book a free 30-minute call and we will review your categories and routing with you.