AI Agent for HOA Management: Meeting Minutes, Violation Tracking, and Resident Communication

HOA Management Is a Communication-Heavy Job

Homeowners associations generate a surprising volume of administrative work: board meeting minutes, violation notices, architectural review requests, community announcements, and resident inquiries. Most HOA managers handle all of this manually with Word documents and email. An AI agent automates the structured parts — summarizing meetings, tracking violations through their lifecycle, and generating consistent communications.

Meeting Minutes Summarization

Board meetings are recorded or transcribed. The agent converts raw transcripts into structured minutes.

from agents import Agent, Runner
from pydantic import BaseModel

class MotionItem(BaseModel):
    description: str
    proposed_by: str
    seconded_by: str
    vote_result: str  # passed, failed, tabled
    vote_count: str   # e.g., "5-2" or "unanimous"

class ActionItem(BaseModel):
    task: str
    assigned_to: str
    deadline: str

class MeetingMinutes(BaseModel):
    meeting_date: str
    attendees: list[str]
    absent: list[str]
    agenda_summary: list[str]
    motions: list[MotionItem]
    action_items: list[ActionItem]
    next_meeting_date: str
    key_discussions: list[str]

minutes_agent = Agent(
    name="MeetingMinutesAgent",
    instructions="""Extract structured meeting minutes from the transcript.
    Capture all motions with exact vote counts.
    Identify action items with clear owners and deadlines.
    Summarize key discussion points objectively without editorial.
    Use formal language appropriate for official HOA records.""",
    output_type=MeetingMinutes,
)

async def generate_meeting_minutes(transcript: str) -> MeetingMinutes:
    """Convert a meeting transcript into structured minutes."""
    result = await Runner.run(
        minutes_agent,
        input=f"Generate meeting minutes from this transcript:\n\n{transcript}",
    )
    return result.final_output

The Pydantic output_type ensures every minutes document has the same structure, making them searchable and consistent across months of board meetings.

Violation Tracking System

HOA violations follow a standard workflow: observation, notice, cure period, follow-up, and possible fines.

from dataclasses import dataclass
from datetime import date, timedelta
from enum import Enum
from typing import Optional

class ViolationStatus(Enum):
    REPORTED = "reported"
    NOTICE_SENT = "notice_sent"
    CURE_PERIOD = "cure_period"
    FOLLOW_UP = "follow_up"
    RESOLVED = "resolved"
    FINED = "fined"
    HEARING_SCHEDULED = "hearing_scheduled"

@dataclass
class Violation:
    violation_id: str
    unit: str
    owner_name: str
    category: str  # landscaping, noise, parking, architectural, trash
    description: str
    reported_date: date
    status: ViolationStatus
    cure_deadline: Optional[date] = None
    fine_amount: Optional[float] = None
    notices_sent: int = 0

def advance_violation_status(violation: Violation) -> Violation:
    """Move a violation to the next stage in the workflow."""
    workflow = {
        ViolationStatus.REPORTED: ViolationStatus.NOTICE_SENT,
        ViolationStatus.NOTICE_SENT: ViolationStatus.CURE_PERIOD,
        ViolationStatus.CURE_PERIOD: ViolationStatus.FOLLOW_UP,
        ViolationStatus.FOLLOW_UP: ViolationStatus.FINED,
    }
    next_status = workflow.get(violation.status)
    if next_status:
        violation.status = next_status
        if next_status == ViolationStatus.CURE_PERIOD:
            violation.cure_deadline = date.today() + timedelta(days=14)
        violation.notices_sent += 1
    return violation

Communication Templates

The agent generates communications from templates, ensuring consistent tone and legal accuracy.

NOTICE_TEMPLATES = {
    "first_notice": """Dear {owner_name},

This letter is to inform you that a violation of the HOA covenants
has been observed at your property ({unit}).

Violation: {category} - {description}
Date Observed: {reported_date}

You have 14 days from the date of this notice to correct
this violation. If not corrected by {cure_deadline}, additional
action may be taken per Article VII of the CC&Rs.

Sincerely,
{hoa_name} Board of Directors""",

    "second_notice": """Dear {owner_name},

This is a second notice regarding the unresolved violation
at your property ({unit}).

Original Notice Date: {first_notice_date}
Violation: {category} - {description}

The cure period has expired. A fine of ${fine_amount} has been
assessed to your account. To contest this fine, you may request
a hearing within 10 days.

Sincerely,
{hoa_name} Board of Directors""",
}

def generate_violation_notice(
    violation: Violation,
    notice_type: str,
    hoa_name: str,
) -> str:
    """Generate a violation notice from a template."""
    template = NOTICE_TEMPLATES.get(notice_type, "")
    return template.format(
        owner_name=violation.owner_name,
        unit=violation.unit,
        category=violation.category,
        description=violation.description,
        reported_date=violation.reported_date,
        cure_deadline=violation.cure_deadline or "TBD",
        fine_amount=violation.fine_amount or 50,
        hoa_name=hoa_name,
        first_notice_date=violation.reported_date,
    )

The HOA Management Agent

from agents import Agent, function_tool

@function_tool
async def summarize_meeting(transcript: str) -> str:
    """Summarize a board meeting transcript into structured minutes."""
    minutes = await generate_meeting_minutes(transcript)
    output = f"Meeting Date: {minutes.meeting_date}\n"
    output += f"Attendees: {', '.join(minutes.attendees)}\n\n"
    output += "Motions:\n"
    for m in minutes.motions:
        output += f"  - {m.description} ({m.vote_result}, {m.vote_count})\n"
    output += "\nAction Items:\n"
    for a in minutes.action_items:
        output += f"  - {a.task} -> {a.assigned_to} by {a.deadline}\n"
    return output

@function_tool
async def report_violation(
    unit: str,
    owner_name: str,
    category: str,
    description: str,
) -> str:
    """Report a new HOA violation."""
    return (
        f"Violation recorded for unit {unit} ({category}). "
        f"First notice will be generated and sent to {owner_name}."
    )

@function_tool
async def get_violation_status(unit: str) -> str:
    """Check the status of violations for a unit."""
    return (
        f"Unit {unit}: 1 active violation\n"
        f"- Landscaping: Dead shrubs in front yard (CURE_PERIOD)\n"
        f"  Deadline: April 1, 2026 | Notices sent: 1"
    )

@function_tool
async def draft_community_announcement(
    topic: str,
    details: str,
) -> str:
    """Draft a community-wide announcement."""
    return (
        f"Subject: {topic}\n\n"
        f"Dear Residents,\n\n{details}\n\n"
        f"Please contact the HOA office with any questions.\n"
        f"Best regards,\nThe Board of Directors"
    )

hoa_agent = Agent(
    name="HOAManagementAgent",
    instructions="""You are an HOA management assistant. Help with meeting
    minutes, violation tracking, and resident communications.
    Always use professional, neutral language. Never express
    opinions on disputes — present facts and process.""",
    tools=[
        summarize_meeting, report_violation,
        get_violation_status, draft_community_announcement,
    ],
)

FAQ

How does the agent handle contested violations?

The agent tracks hearing requests as a status in the violation workflow. When an owner requests a hearing, the agent schedules it, sends notification to the board and the owner, and prepares a hearing packet with the violation history, photos, and correspondence. The board makes the final decision.

Can the meeting minutes agent handle multiple speakers in a transcript?

Yes. The agent identifies speakers from the transcript context (e.g., "Board President Smith said...") and attributes motions and comments to the correct individuals. For cleaner results, use a transcription service that provides speaker diarization.

Is there a risk of bias in AI-generated violation notices?

The notices are generated from standardized templates, ensuring every resident receives identical language for the same type of violation. The AI fills in facts (dates, descriptions, deadlines) but does not modify the legal language. This is actually more consistent than manually written notices.

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