AI tailors event invitations based on each recipient's interests and past attendance. Marketing reviews before every send.
Generic event invitations have low open and registration rates because they feel mass-produced. Personalizing invitations at scale is impossible without automation — but fully automated sends risk off-brand messaging or targeting the wrong audience segments.
MultiMail's AI agent segments your audience, personalizes each invitation based on recipient interests and past event attendance, and queues everything for marketing review. Gated_send oversight ensures every invitation is on-brand and properly targeted before delivery.
Set up the event details — date, speakers, topics, registration link. The AI agent uses search_contacts to identify the target audience based on interest tags and engagement history.
The agent groups recipients by interest, role, and past attendance, then crafts a unique pitch for each segment highlighting the most relevant speakers or topics.
Using send_email, the agent composes personalized invitations for each recipient with tailored subject lines, opening hooks, and calls to action.
With gated_send oversight, all invitations enter the approval queue. Marketing reviews messaging, targeting, and branding before approving for delivery.
import requests
API = "https://api.multimail.dev/v1"
HEADERS = {"Authorization": "Bearer mm_live_xxx"}
response = requests.post(
f"{API}/send",
headers=HEADERS,
json={
"from": "[email protected]",
"to": ["[email protected]"],
"subject": "You&"cm">#039;re invited: Building AI agents with email (March 20 webinar)",
"text_body": (
"Hi Rachel,\n\n"
"Based on your interest in agent frameworks, I thought you&"cm">#039;d "
"enjoy our upcoming webinar on building AI agents with email "
"capabilities.\n\n"
"Date: March 20, 2026 at 2pm ET\n"
"Speaker: Jane Smith, Head of AI Platform\n\n"
"Register here: https://events.yourcompany.com/webinar-march\n"
),
"html_body": "<h2>You&"cm">#039;re Invited</h2><p>Hi Rachel...</p>"
}
)
print(f"Invitation queued: {response.json()[&"cm">#039;id']}")Compose and send a personalized webinar invitation through the MultiMail API.
import requests
API = "https://api.multimail.dev/v1"
HEADERS = {"Authorization": "Bearer mm_live_xxx"}
"cm"># Find contacts interested in AI agents
ai_segment = requests.get(
f"{API}/contacts/search",
headers=HEADERS,
params={"query": "ai-agents"}
).json()
"cm"># Find contacts interested in developer tools
dev_segment = requests.get(
f"{API}/contacts/search",
headers=HEADERS,
params={"query": "developer-tools"}
).json()
print(f"AI segment: {len(ai_segment[&"cm">#039;results'])} contacts")
print(f"Dev segment: {len(dev_segment[&"cm">#039;results'])} contacts")Search contacts by interest tags to build targeted invitation lists.
"cm">// Find contacts interested in the event topic
const audience = await mcp.search_contacts({
query: "ai-agents",
limit: 200
});
"cm">// Send personalized invitations
for (const contact of audience.results) {
const result = await mcp.send_email({
to: contact.email,
subject: `${contact.name}, join our AI agents webinar March 20`,
text_body: `Hi ${contact.name}, based on your work in AI...`
});
"cm">// Tag for campaign tracking
await mcp.tag_email({
email_id: result.id,
tags: ["event-invite", "webinar-march-2026"]
});
}Use MCP tools to search contacts, send invitations, and tag for tracking.
Personalized invitations that reference the recipient's interests and role outperform generic blasts. AI makes personalization at scale practical.
Gated send ensures marketing reviews every invitation before delivery. No off-brand messaging or incorrect event details reach your audience.
AI segments your contact list by interest, engagement history, and past event attendance, ensuring invitations reach the most relevant recipients.
The agent automatically sends reminder emails to non-respondents and confirmation details to registrants, maintaining engagement throughout the event lifecycle.
Email infrastructure built for AI agents. Verifiable identity, graduated oversight, and a 38-tool MCP server. Formally verified in Lean 4.