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AI Integration

Sorting, Summarising and Drafting Email Automatically

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Shared inboxes are the hidden cost centre

info@, sales@, accounts@ and the rest. Nobody owns them, everybody checks them, and the same message gets read three times before anyone acts.

It is unglamorous, high-volume, low-risk work — which makes it very good ground for automation.

Four things worth automating

  1. Classification and routing on arrival, with a label and an owner
  2. Thread summaries for anything over four messages
  3. Draft replies for the routine categories, saved as drafts
  4. Data extraction — orders, enquiries, changes — into your systems
The fourth is the one people forget and the one that pays. An enquiry that becomes a CRM record without anyone retyping it is pure saving.

Do not send automatically

Draft, do not send. The reputational cost of one wrong automatic reply exceeds the time saved by hundreds of right ones.

After six months of measured acceptance rates on a narrow category, automatic sending becomes a reasonable conversation. Not before.

Handling the awkward cases

  • Complaints escalated immediately, never drafted automatically
  • Legal or regulatory language routed to a named person
  • Anything mentioning money owed, flagged rather than answered
  • Out-of-office and bounce noise suppressed entirely

Practical setup

Works with Microsoft 365 and Google Workspace through their APIs. Nothing needs to be installed on anyone's machine and nothing changes about how they read mail.

Typical build is two to four weeks, and the classification alone usually justifies it.

Frequently asked questions

Does it read everyone's personal email?

No. Scope it to shared mailboxes only, and say so plainly to the team. Scope creep here damages trust quickly.

What about attachments?

Extraction from attached documents is often the highest-value part — orders and invoices arriving as PDFs into a shared inbox.

Can it handle our reply templates?

Yes, and it works better with them. Existing templates give it structure and voice to work from.

How accurate is the routing?

Typically 90–96% on clear categories after tuning. Ambiguous categories are usually a labelling problem rather than a model one.

Keep reading

A shared inbox nobody owns?

It is usually the cheapest automation available. Tell us the volume and the categories you wish existed.

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