AI-powered support for homeowner associations

The challenge

Managing homeowner associations means dealing with a constant stream of resident inquiries. Noise complaints, maintenance requests, parking issues, questions about house rules, billing disputes — the same types of questions come in week after week.

Abovve.nl, a Dutch software platform for HOA (VvE) administrators, was spending a disproportionate amount of time on support emails. Their users handle hundreds of tickets monthly across multiple associations, and the vast majority were repetitive questions with straightforward answers.

"About 70% of our incoming emails are questions we've answered dozens of times before," their operations lead explained. "What are the parking rules? When is the next residents' meeting? How do I submit a maintenance request? We needed a way to handle these automatically without losing the personal touch for complex issues."

The solution

Abovve built an agentic email support workflow using EmailConnect and n8n. Each association gets a dedicated support alias like support-parkview@ingest.abovve.nl. When a resident sends an email, here's what happens:

1. EmailConnect parses the incoming email — extracting the resident's message, sender details, subject, and any attachments
2. n8n receives the webhook and passes the parsed content to an AI classification node
3. The AI analyzes the ticket against the association's knowledge base (house rules, FAQ, meeting minutes, maintenance procedures) and generates a response with a confidence score
4. High confidence (>85%) — the response is sent automatically as a reply to the resident
5. Lower confidence — the ticket is routed to a human administrator with the AI's suggested response as a draft

Step 1: EmailConnect delivers the parsed email

When a resident sends an email to the association's support alias, EmailConnect parses it and fires the webhook:

{
  "message": {
    "date": "2026-01-15T09:01:44.000Z",
    "sender": {
      "name": "J. Jansen",
      "email": "j.jansen@gmail.com"
    },
    "recipient": {
      "email": "support-parkview@ingest.abovve.nl"
    },
    "subject": "Parking spot rules for visitors",
    "content": {
      "text": "Hi, my parents are visiting this weekend. Can they use the visitor parking spots? How long are they allowed to park there?",
      "markdown": "Hi, my parents are visiting this weekend. Can they use the visitor parking spots? How long are they allowed to park there?"
    },
    "attachments": []
  },
  "classification": {
    "type": "normal",
    "confidence": "definite"
  }
}

Showing relevant fields only. See the full webhook payload reference →

Step 2: n8n classifies and decides

The n8n workflow receives the webhook, passes the message to an LLM node along with the association's knowledge base, and gets back a classification with confidence score:

• Association identified — the recipient alias (support-parkview) maps to the Parkview knowledge base
• AI classifies the question — "parking / visitor rules" matched against house rules section 4.2
• Confidence: 94% — above the 85% threshold, so the response will be sent automatically

Step 3: The result — automatic response

Because the confidence is high, the resident gets an instant reply:

{
  "action": "auto_sent",
  "confidence": 0.94,
  "matched_policy": "house_rules_section_4.2",
  "response": "Hi! Visitors are welcome to use the designated visitor spots (P12-P16). They can park for up to 72 hours. For longer stays, please register at the front desk or email us so we can reserve a temporary spot. Have a nice weekend with your parents!",
  "sent_at": "2026-01-15T09:03:12Z"
}

When confidence is low: human-in-the-loop

Not every ticket gets an automatic response. When a resident reports something complex — say water damage from an upstairs neighbor — the same three steps play out, but with a different outcome:

The EmailConnect payload arrives the same way. The AI classifies it as "maintenance / water damage between units" but only scores 62% confidence — below the threshold. Instead of auto-sending, the n8n workflow routes the ticket to a human administrator with the AI's suggested draft:

{
  "action": "routed_to_human",
  "confidence": 0.62,
  "reason": "Complex liability — involves multiple units, potential insurance claim, requires inspection",
  "suggested_draft": "Dear Mr. de Vries, thank you for reporting this. Water damage between units requires immediate attention. I've flagged this as urgent and our maintenance coordinator will contact you within 2 hours to arrange an inspection. In the meantime, please document the damage with photos.",
  "assigned_to": "admin_team",
  "priority": "urgent"
}

The administrator sees the AI's draft, the confidence score, and the reasoning — then can approve, edit, or rewrite the response before it goes out. Over time, approved responses feed back into the knowledge base, making the AI smarter.

Why this works

• Common questions get instant answers — residents don't wait hours for parking rules or meeting dates
• Complex issues get human attention — water damage, disputes, and billing problems always involve a person
• The AI learns over time — every human-edited response improves future accuracy
• Per-association knowledge bases — each HOA has its own rules, and the AI knows the difference
• Full transparency — residents can always reach a human by replying to any automated message

The results

Support ticket handling went from a time sink to a streamlined, partially autonomous operation.

• 60% reduction in ticket handling time — administrators focus on complex cases that actually need human judgment
• Residents get instant answers to common questions — no more waiting until business hours
• Consistent quality — every response is based on the actual house rules and policies
• Scalable across associations — adding a new HOA means adding a knowledge base and an alias
• Human oversight preserved — the AI never handles anything it's not confident about