AI monitors your service levels and sends instant alerts when metrics approach contractual thresholds. Prevent penalties before they happen.
SLA breaches discovered after the fact damage customer trust and trigger contractual penalties that can cost thousands per incident. Manual monitoring is reactive — by the time someone notices a metric has dipped below the threshold, the breach has already occurred and the penalty is locked in.
MultiMail's AI agent monitors SLA metrics in real time and sends proactive alerts when thresholds are approaching. Autonomous mode ensures zero delay on time-critical warnings, giving your team a window to remediate before contractual breaches actually occur.
Configure your SLA thresholds — uptime percentages, response times, resolution windows. The AI monitors these metrics and calculates proximity to breach in real time.
When a metric enters the warning zone (e.g., uptime drops to 99.7% against a 99.5% SLA), the AI immediately composes an alert with current metrics, trend data, and contributing incidents.
In autonomous mode, the alert is sent immediately to stakeholders — engineering leads, customer success managers, and account executives. No approval delay on time-critical warnings.
If metrics actually breach the SLA threshold, the agent sends escalation notifications to executives with impact analysis, affected customers, and potential penalty exposure.
import requests
API = "https://api.multimail.dev/v1"
HEADERS = {"Authorization": "Bearer mm_live_xxx"}
def check_sla_metrics(metrics: dict, thresholds: dict):
for metric, value in metrics.items():
threshold = thresholds[metric]
if value <= threshold["warning"]:
alert_body = (
f"SLA Warning: {metric} is at {value}, "
f"approaching threshold of {threshold[&"cm">#039;breach']}.\n\n"
f"Contributing factors:\n{get_recent_incidents(metric)}\n\n"
f"Action needed to prevent breach."
)
requests.post(
f"{API}/send",
headers=HEADERS,
json={
"from": "[email protected]",
"to": "[email protected]",
"subject": f"[SLA WARNING] {metric} at {value}",
"text_body": alert_body
}
)
check_sla_metrics(
{"api_uptime": 99.7, "p99_latency_ms": 450},
{"api_uptime": {"warning": 99.7, "breach": 99.5},
"p99_latency_ms": {"warning": 400, "breach": 500}}
)Detect when metrics approach SLA thresholds and alert the team before a breach occurs.
import requests
API = "https://api.multimail.dev/v1"
HEADERS = {"Authorization": "Bearer mm_live_xxx"}
def escalate_sla_breach(metric: str, value: float, affected_customers: list):
body = (
f"SLA BREACH: {metric} has fallen to {value}.\n\n"
f"Affected customers: {len(affected_customers)}\n"
f"Estimated penalty exposure: ${calculate_penalties(affected_customers):,}\n\n"
f"Immediate action required."
)
"cm"># Notify executives
for recipient in ["[email protected]", "[email protected]"]:
requests.post(
f"{API}/send",
headers=HEADERS,
json={
"from": "[email protected]",
"to": recipient,
"subject": f"[SLA BREACH] {metric} - {len(affected_customers)} customers affected",
"text_body": body
}
)Send escalation notifications when an SLA is actually breached, including penalty exposure.
"cm">// SLA breach alert workflow via MCP
const metrics = await getServiceMetrics();
if (metrics.apiUptime <= 99.7) {
"cm">// Send warning alert
await mcp.send_email({
from: "[email protected]",
to: "[email protected]",
subject: `[SLA WARNING] API uptime at ${metrics.apiUptime}%`,
text_body: `API uptime has dropped to ${metrics.apiUptime}%, approaching the 99.5% SLA threshold. Recent incidents: ${metrics.recentIncidents.join(", ")}`
});
"cm">// Tag for tracking
await mcp.tag_email({
email_id: alert.id,
tags: ["sla-warning", "api-uptime"]
});
}Use MultiMail MCP tools for SLA monitoring and alerting.
Early warning alerts give your team time to remediate issues before metrics actually breach contractual SLA thresholds.
Autonomous mode sends SLA warnings instantly. When you're 0.2% away from a breach, every minute of delay matters.
AI enriches alerts with contributing incidents, trend data, and affected customer counts so the team can prioritize response immediately.
Automatic escalation to executives when breaches occur, including penalty exposure calculations and affected customer lists.
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