Solution
Alerts & monitoring from your database
Get notified when data changes. Catch problems before they escalate. Never miss a critical business event.
What you can monitor
Threshold alerts
Get notified when metrics cross thresholds. Inventory levels, revenue targets, error rates.
Anomaly detection
AI detects unusual patterns. Spike in refunds, drop in signups, unexpected behavior.
Status change alerts
Monitor state transitions. Deal stage changes, order status updates, user lifecycle events.
Scheduled checks
Run queries on schedules. Daily summaries, weekly reports, monthly executive digests.
Alert channels
Slack
Direct message or channel
Individual or distribution list
SMS
Critical alerts only
Webhook
Custom integrations
Alert use cases
Sales
- • Large deal closed
- • Deal stuck too long
- • Pipeline threshold reached
- • Quota attainment alerts
Operations
- • Low inventory warning
- • Order backlog growing
- • SLA breach imminent
- • System health metrics
Customer Success
- • Churn risk detected
- • Usage dropped significantly
- • Support tickets spiking
- • Renewal upcoming
Frequently asked questions
How do database alerts work?
AI for Database continuously monitors your database based on conditions you define in plain English. When a condition is met — such as inventory dropping below a threshold, revenue exceeding a target, or an anomaly in user behavior — the platform sends a notification via Slack, email, SMS, or webhook. Alerts run on a schedule you choose, from every minute to daily checks, so you catch critical changes as they happen.
Can AI detect anomalies in my database automatically?
Yes. AI for Database includes anomaly detection that identifies unusual patterns in your data by comparing current values against historical baselines. It can detect spikes in refund rates, drops in signups, unexpected changes in order volume, and other deviations that exceed normal variance. You receive alerts only when deviations are statistically significant, reducing noise and false positives.
What alert channels are supported?
AI for Database supports Slack (direct messages and channels), email (individual addresses and distribution lists), SMS for critical alerts, and webhooks for custom integrations. You can route different alert types to different channels — for example, critical inventory alerts to SMS and daily summary reports to email. Each alert includes the relevant data context so you can act immediately without logging in.
How is this different from application monitoring tools like Datadog?
Application monitoring tools like Datadog track infrastructure metrics such as CPU, memory, and error rates. AI for Database monitors your business data — revenue, orders, customer behavior, inventory levels, and operational KPIs. It is designed for business users who need alerts on data changes that matter to the business, not DevOps engineers monitoring server health. The two are complementary rather than competing.