- Build time
- 5 to 9 days
- Visual motif
- Reasoning orbit
- Architecture basis
- Email Triage Agent for Service Inquiries uses a bounded agent handoff layer for AI Agents. An agent that reads inbound service emails, classifies and prioritizes them, extracts the key details, and labels or routes each to the right perso... The architecture connects agree the category taxonomy, gmail / outlook api, gpt-5-class classification +, and agent handoff with an explicit control path.
Email Triage Agent for Service Inquiries
AI Email
An agent that reads inbound service emails, classifies and prioritizes them, extracts the key details, and labels or routes each to the right person with a suggested reply.
Build time 5 to 9 days
HMX Zone
ai agent case study
AI Email
Verified HMX-owned case details.
outcomes
- Auto-sorted
- Inbox triaged by type and urgency on arrival
- Owner routing
- Each email reaches the right person, not a shared void
- Draft-ready
- Common replies pre-written for one-click approval
- Lead capture
- New inquiries logged to the CRM automatically
case architecture
Email Triage Agent for Service Architecture
- 01Agree the category taxonomy
An agent that reads inbound service emails, classifies and prioritizes them, extracts the key details, and labels or routes each to the right perso...
- 02extraction that pulls sender
Build extraction that pulls sender intent, urgency, and the concrete ask into structured fields.
- 03Gmail / Outlook API
Gmail / Outlook API runs the bounded conversation step for Email Triage Agent for Service while keeping tool use, transcripts, and escalation outcomes explicit.
- 04GPT-5-class classification +
Apply labels and route to per-owner queues; create a CRM lead for new-inquiry emails.
- 05Human Escalation
When automation confidence is low, route the record to a manual owner with the source, stage, and last action attached.
- 06Agent Handoff
Auto-sorted Inbox triaged by type and urgency on arrival; Owner routing Each email reaches the right person, not a shared void; Draft-ready Common...
problem and build
problem
The operating gap
A shared inbox fills with mixed inquiries: new leads, existing customers, suppliers, and spam. Triage is manual, urgent requests sit unseen, and details get lost when messages are forwarded around.
build
What gets built
An agent processes each new email, classifies it (new lead, support, billing, partnership, noise), extracts structured fields (who, what, urgency, requested action), applies a label, and routes it to the owning person or queue. For common types it drafts a reply for one-click human approval; it never auto-sends on sensitive categories. Low-confidence items are flagged 'needs human triage' rather than mis-filed.
build steps
- 01Agree the category taxonomy and which categories may get an auto-draft vs must stay human-only.
- 02Build extraction that pulls sender intent, urgency, and the concrete ask into structured fields.
- 03Apply labels and route to per-owner queues; create a CRM lead for new-inquiry emails.
- 04Generate suggested replies for safe categories as drafts, never sending without approval.
- 05Add a confidence gate that diverts unclear emails to a manual triage label.
- 06Review misclassifications weekly and refine the prompts and category rules.
architecture notes
Architecture layers
- Conversation layer: Agree the category taxonomy and which categories may get an auto-draft vs must stay human-only.
- Reasoning layer: Build extraction that pulls sender intent, urgency, and the concrete ask into structured fields.
- Tools layer: Gmail / Outlook API runs the bounded conversation step for Email Triage Agent for Service while keeping tool use, transcripts, and escalation outcomes explicit.
- Records layer: GPT-5-class classification + extraction connects calls, messages, calendar work, or CRM writes while an agent processes each new email, classifies it (new lead, support, billing, partnership, noise), extracts structured fields (who, what, urgency,...
- Escalation layer: Auto-sorted Inbox triaged by type and urgency on arrival; Owner routing Each email reaches the right person, not a shared void; Draft-ready Common...
Data flow
- Agree the category taxonomy and which categories may get an auto-draft vs must stay human-only.
- Build extraction that pulls sender intent, urgency, and the concrete ask into structured fields.
- Apply labels and route to per-owner queues; create a CRM lead for new-inquiry emails.
- Generate suggested replies for safe categories as drafts, never sending without approval.
- Add a confidence gate that diverts unclear emails to a manual triage label.
- Review misclassifications weekly and refine the prompts and category rules.
Controls and fallbacks
- A shared inbox fills with mixed inquiries: new leads, existing customers, suppliers, and spam.
- An agent processes each new email, classifies it (new lead, support, billing, partnership, noise), extracts structured fields (who, what, urgency,...
- When automation confidence is low, route the record to a manual owner with the source, stage, and last action attached.
Stack
- Gmail / Outlook API
- GPT-5-class classification + extraction
- Make or n8n
- Label/folder routing
- CRM lead creation (GoHighLevel)
- Human approval step for drafts
research basis
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