Know the moment something breaks.
Spot outliers in any time series. Tell a real incident apart from an expected seasonal swing.
Built for signals worth acting on.
An alert nobody trusts is worse than no alert at all.
Catch it early
Alerts the moment a metric leaves the range it normally sits in.
Learns your patterns
Adapts to weekly and seasonal cycles instead of fixed thresholds.
Fewer false alarms
Expected seasonal swings are filtered out, so alerts stay meaningful.
Built for your monitoring stack.
One endpoint. Send the series, get the outliers back.
curl -X POST https://forecastapi.com/v2/detect-anomalies \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"identifier": "cpu-prod-01",
"frequency": "D",
"data": [
{"date": "2024-01-01", "value": 42},
{"date": "2024-01-02", "value": 46},
{"date": "2024-01-03", "value": 312}
],
"anomaly_settings": {"method": "auto", "threshold": 3.0}
}'
# Response
{
"result": {
"anomalies": [
{
"date": "2024-01-03",
"value": 312,
"type": "spike",
"severity": "high",
"z_score": 4.12,
"expected_range": [38.2, 61.4],
"deviation_percentage": 528.6
}
],
"analysis": {"method_used": "z_score", "confidence": "high"}
},
"meta": {"timing": {"total": 142.3}}
}
Detection and integrations included.
Four detection methods
auto, z-score, IQR, seasonal
Seasonal awareness
Weekly, monthly, and holiday cycles
Severity scoring
Spike or dip, ranked by deviation
Tunable sensitivity
Thresholds from 0.5 to 5.0
Streaming support
Detect as the data arrives
Monitoring tools
Datadog, New Relic, Grafana
Alerting
PagerDuty, Slack, Microsoft Teams
Time series stores
Prometheus, InfluxDB, Elasticsearch
Critical decisions, made easier.
Where catching it early changes the outcome.
Incident response
Catch the regression before the first support ticket.
Alert thresholds
Replace static limits with ranges learned from the data.
Capacity checks
Spot resource drift long before it saturates.
Revenue monitoring
Notice a conversion drop the day it starts.
Data quality
Flag broken pipelines when values go implausible.
Maintenance planning
Act on sensor drift before the equipment fails.
Trusted across industries.
From DevOps to business intelligence, anywhere a number can go wrong.
System & infrastructure
CPU, memory, and network watched for early warning signs.
Business intelligence
Unusual movement in sales, engagement, and conversion.
IoT & sensors
Temperature, vibration, and environmental data for predictive maintenance.
Pay only for what you use.
Scale your detection as you grow.
Catch it before it breaks.
Join the teams monitoring with ForecastAPI.
Your first 200 calls are free, no credit card required.