AI Email Automation — Classification, Replies, Escalations
AI email automation replaces the morning inbox triage — a system that reads every incoming message, classifies it ("inquiry", "quote", "complaint", "invoice"), drafts a reply in your company's tone and escalates priority cases to a specific human. We connect to Gmail and Outlook through their official APIs, train the model on your Sent folder, and reach 80% automated triage and roughly 12 minutes saved per employee per day. No per-seat subscription, no forwarding your mail to a third-party chatbot platform — backend, prompts and embeddings stay with you.
What the AI email assistant actually replaces
This is not an auto-responder or a rule like "if the subject contains X, move to folder Y". It is an LLM layer over your mailbox that understands the message, the prior thread and your internal rules for who owns what. It replaces the first 20-30 minutes of morning triage that every salesperson, office manager or customer success rep loses before the real work starts.
- ✓Inbox classification into categories — every new email gets a label ("inquiry", "quote", "order", "complaint", "invoice", "spam", "internal") in under 2 seconds, with 92%+ accuracy after the first 500 examples from your mail.
- ✓Draft replies in your voice — the assistant learns from your Sent folder — typical phrases, greetings, signatures, level of formality — and queues a draft a human reviews in 20-40 seconds before hitting Send.
- ✓Priority escalations to a named person — VIP customer, big order, keywords like "lawsuit", "cancel", "bad review" — the email routes straight to Slack/Teams or a push to the responsible owner's phone.
- ✓Native Gmail and Outlook integration — Google Workspace API and Microsoft Graph, OAuth2 on your behalf, no IMAP passwords, no forwarding to an external server. Full audit and access control remain yours.
- ✓Structured data extraction — contact name, company, VAT, product, quantity, requested date land directly as a new record in your CRM or ERP. The inquiry is quote-ready with no copy-paste.
- ✓Learning from your edits — every change you make to a draft before sending feeds back as a new example. After 4-6 weeks, 70%+ of drafts go out with minimal edits.
- ✓Weekly mailbox report — volume, average response time, top recurring topics worth turning into FAQs or templates. Real B2B impact, not vanity metrics.
This sits inside the broader business process automation work we do — email is one of several channels we can offload.
Who it works for
60-200 inquiries a day, half of them repetitive — price, availability, lead time, specs. AI reads the message, replies with real data from your ERP, and leaves only the hot deals for a human. Result: 30-45% faster time from inquiry to quote, no leads dropped on holidays.
A support@ inbox with 100+ messages a day — "where is my order", "how do I return", "feature X broken". The system pulls the order number, checks ERP status, drafts a fact-grounded reply and queues it. About 80% triaged automatically, the rest get priority human attention.
Law firms, construction, medical centers — a flood of invoices, quotes, contracts and internal questions. The AI email assistant labels incoming mail, routes invoices to the accountant, contracts to legal, and saves roughly 12 minutes per person per day from inbox digging.
How we deliver it
Always the same shape: four to six weeks from kick-off to production, no big-bang switch. Week one the system only classifies and suggests — nothing leaves automatically. We connect via the official Gmail or Outlook API, not IMAP, and all data stays on our own EU backend.
1. Inbox audit
We pull an anonymized sample of the last 1000-3000 emails under NDA, segment by topic and measure real volume — messages per day, average response time, top-10 repeat topics. This is the ROI baseline.
2. Categories and escalation rules
Together we lock down 8-15 categories and the rules — what is a VIP customer, what counts as a complaint, what goes straight to management. We talk in business language: "if a customer writes twice about the same problem, escalate" is a valid instruction.
3. RAG and Sent-folder training
We embed the last 2000-5000 sent emails from key people into a vector store, so drafts sound like them — concise, polite, with the correct product names. This is the difference between "another AI reply" and an email a customer cannot tell from a hand-written one.
4. Pilot with double approval
For the first 2-3 weeks nothing sends without a human click. We watch classification accuracy and draft quality. Once metrics stabilize above the agreed threshold (typically 90% accurate labels, 70% drafts sent without edits), we enable auto-send for low-risk categories — order status, catalog prices, basic FAQs.
Why Saitami
Fixed EUR pricing, no per-mailbox subscriptions. For wider scope see AI agent for business processes and AI chatbot for customer service, or the playbook in how to automate customer requests.
Frequently asked questions
Will the AI "read" all our mail — what about GDPR?
Data stays in the EU. The backend runs on servers in Frankfurt or Amsterdam, and the Gmail/Outlook connection is over the official OAuth2 API, not forwarding. Embeddings and logs live with you, not at OpenAI or Anthropic — we only send the specific message text for inference, and it is excluded from third-party training. We sign a DPA, configure retention and role-based access. With correct implementation, AI email automation is fully GDPR-compatible.
What if the AI misclassifies an important email?
In the first weeks nothing sends automatically — everything is human-approved. After the pilot we whitelist the categories allowed to auto-send (typically order status, receipt confirmations, catalog prices). Everything else stays in a review queue. A wrong label is one click to correct, and the model learns from it. After 4-6 weeks, error rate drops below 5%.
Does it work with on-prem Exchange or only Microsoft 365?
Microsoft 365 (cloud Outlook) and Google Workspace are supported directly via Microsoft Graph and the Gmail API. For on-prem Exchange we connect via EWS — feasible but adds roughly a week of DevOps during setup. Hybrid setups (Exchange + 365) usually benefit from moving fully to the cloud before launch to keep long-term support simpler.
What is the real cost of AI email automation?
From €2,400 for one mailbox or shared inbox — classification, drafts, escalation, basic integration with one external system (CRM or ERP). Multi-mailbox with Sent-folder RAG and complex escalation rules starts from €4,800. Recurring cost is just API tokens and hosting, typically €40-€180/month depending on volume. No per-seat or per-message fees.
How long does full rollout take?
4-6 weeks for one inbox at standard complexity: week 1 audit and categories, week 2 integration and RAG, weeks 3-4 pilot with double approval, weeks 5-6 enabling auto-send for selected categories. First measurable savings (6-8 minutes per person per day) show up during the pilot itself.
Ready to give every employee 12 minutes back per day?
Send us an anonymized sample of 50-100 typical emails (or just a description of the flow) and within 5 business days you get a concrete plan — categories, timeline, fixed EUR price and projected time savings.
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