Real-time anomaly detection

Statistical + ML models flag deviations within seconds of ingestion, with confidence scores instead of blind thresholds.

Predictive forecasting

Rolling forecasts on every core metric, retrained nightly against your live pipeline — no manual model tuning.

Automated reporting

Digest reports land in Slack or email on your schedule, written in plain language, not just charts.

Root-cause explanations

Every alert ships with a plain-language explanation of contributing factors — not just a spike on a chart.

Pipeline health monitoring

Track schema drift, ingestion delay, and data quality across every source feeding your warehouse.

Enterprise-grade security

SOC 2 Type II, column-level access control, and full audit logging on every workspace, by default.

How it works

From raw event to explained anomaly in three steps

01

Connect your pipeline

Point Agent Forge AI at your warehouse, event stream, or API in minutes with pre-built connectors.

02

Models learn your baseline

Within 48 hours, forecasting and anomaly models are calibrated to your specific traffic patterns.

03

Get explained alerts

When something shifts, you get a plain-language explanation — not just a red dot on a graph.

Integrations

Plugs into the stack you already run

Native connectors for warehouses, event streams, and alerting tools — most teams are ingesting live data within 15 minutes.

SF
Snowflake
Warehouse
BQ
BigQuery
Warehouse
RS
Redshift
Warehouse
DB
Databricks
Lakehouse
PG
PostgreSQL
Database
KF
Kafka
Event stream
SG
Segment
CDP
FT
Fivetran
Ingestion
DBT
dbt
Transform
S3
Amazon S3
Storage
SL
Slack
Alerting
PD
PagerDuty
Alerting
Don't see your tool? Our REST API and webhooks connect to anything.
Built for every team

The same pipeline, tuned to how you work

Catch pipeline breakage before your CEO does

Agent Forge AI watches ingestion jobs and schema contracts across every source so silent failures don't reach the warehouse.

  • Schema drift detection across every ingested table
  • Freshness & volume anomaly alerts before dashboards break
  • Lineage-aware root cause across upstream dependencies
Pipeline health
events_raw → events_cleanHealthy
orders_stream ingestionHealthy
users_dim schema checkHealthy
Last full scan38 seconds ago

Know why activation dropped, same day

Funnel and cohort metrics are monitored continuously, with root-cause breakdowns by platform, geography, and release version.

  • Automatic segment breakdowns on every metric drop
  • Release-correlated anomaly tagging
  • Weekly plain-language product health digest
Activation funnel
Signup → Activated+4.2%
iOS activation rateHealthy
Android activation rateHealthy
Root cause confidence96%

Forecast pipeline and revenue without a spreadsheet

Rolling forecasts on bookings, churn, and pipeline coverage, retrained nightly against your live CRM and billing data.

  • 14-day and 90-day revenue forecasts, auto-updated nightly
  • Churn-risk scoring surfaced before renewal windows
  • Automated board-ready reporting, no manual exports
Revenue forecast
Q3 bookings forecastOn track
At-risk accounts flagged12
Forecast accuracy (90d)94.1%
Next model retrainTonight, 02:00 UTC

Reduce alert fatigue with confidence-scored anomalies

Latency, error rate, and throughput anomalies are correlated across services, so on-call gets one explained incident instead of twenty noisy pages.

  • Cross-service correlation collapses duplicate alerts
  • PagerDuty & Slack routing with confidence thresholds
  • Post-incident timeline auto-generated for retros
Incident correlation
Checkout API p99 latencyResolved
Alerts collapsed into 1 incident19
Time to root cause4m 12s
On-call pages sent1 (was 19)
Under the hood

Technical specs, not marketing rounding

Ingestion latency
< 2 seconds
Event-to-availability time for streaming sources under normal load.
Model retraining
Nightly, per workspace
Forecasting and anomaly baselines recalibrate against your latest data automatically.
API & webhooks
REST + GraphQL
Full read/write API plus outbound webhooks for every alert and report.
SDKs
Python, Node, Go
First-party client libraries for custom ingestion and query workflows.
Data residency
US, EU, APAC
Choose the region your data is processed and stored in at workspace creation.
Encryption
AES-256 / TLS 1.3
At rest and in transit, with customer-managed key support on Enterprise.
Why not just use a dashboard?

How Agent Forge AI compares

CapabilityLegacy BI dashboardsGeneric alerting toolsAgent Forge AI
Anomaly detectionManual thresholdsYesYes, ML-scored
Root-cause explanationPlain-language, automatic
ForecastingNightly, per metric
Setup timeWeeksDaysMinutes
Ongoing maintenanceDashboard sprawlAlert fatigueSelf-calibrating

See these features on your own data

Run a live analysis pass on our demo pipeline right now — no signup required.