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/// integration pair · anomaly detection

Anomaly Detection: GitHub + WordPress

How fast do you find out when something breaks?

GitHub · LIVE + WordPress · LIVE Detection Module · Anomaly Detection
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The problem

Something shifted last Tuesday. Nobody noticed until Friday's report. By then you'd already lost five days of revenue. The data was there. Nobody was watching.

GitHub tracks commits and pull requests, deployment events, release tags. WordPress tracks page and post performance, content categories and tags, user engagement metrics. Neither sees the other. That blind spot costs you money every day.

How askotter fixes this

askotter pulls GitHub and WordPress into one data lake. With both data sets unified, it can catch metric changes in minutes, not days. Self-healing agents adapt as your data shifts, so the analysis stays accurate without manual tuning.

Alerts within minutes. With context: what changed, how severe, and what to check first. Self-healing agents adjust thresholds and re-route alerts as your patterns shift.

What feeds anomaly detection

FROM GITHUB
→ Commits and pull requests
→ Deployment events
→ Release tags
→ Repository activity
→ Issue tracking
→ Code review data
→ CI/CD pipeline status
→ Branch and merge activity
FROM WORDPRESS
→ Page and post performance
→ Content categories and tags
→ User engagement metrics
→ Form and CTA interactions
→ Plugin data
→ Site speed metrics
→ Internal search queries
→ Content publish schedule

What happens when they're connected

Separately, each tool answers its own questions. Together in one lake, askotter can answer the questions that matter: the ones that span both. Train these agents like your best employee and they become tireless assistants that scale your team's knowledge to everyone.

01

Correlates deployment timing with changes in customer behavior

02

Connects revenue anomalies to specific deployments

03

Shows which WordPress pages appear in paths that end in purchases

Before and after

CapabilityWithout askotterWith askotter
Anomaly DetectionManual, delayedAutomatic, real-time
Cross-platform dataCopy-paste between tabsOne data lake
Change detectionWeekly reportMinutes
Next stepsFigure it out yourselfRanked actions, human-approved
QueryingSQL or export to CSVAsk in plain English
Team knowledgeTribal knowledge, lost in SlackSaved notes, shared across teams
/// inside the platform

Anomaly Detection in action

🔒 app.askotter.ai/insights/
ANOMALY DETECTION
RAW DATA
HISTORY
How fast do you find out when something breaks?
Analysis complete. Using data from GitHub and WordPress:
Alerts within minutes. With context: what changed, how severe, and what to check first. Self-healing agents adjust thresholds and re-route alerts as your patterns shift.
GitHub WordPress Detection
github · sync statusCONNECTED
STATUS
● Synced
DATA POINTS
8
LAST SYNC
2m ago
LIVECommits and pull requestssynced
LIVEDeployment eventssynced
LIVERelease tagssynced
LIVERepository activitysynced

Ask your data lake anything. Save what matters.

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