Catches what dashboards miss

Not threshold alerts that fire on noise. AI-powered triggers that learn your patterns and only surface what actually matters.

What you get:

• Adaptive frequency. The system adjusts how often it checks based on how fast things are changing. Quiet week? Checks less. Performance shifting? Checks more. You set the min and max bounds.
• Sensitivity levels. Low (only critical findings), Medium (noteworthy changes), or High (comprehensive monitoring). Tune the signal-to-noise ratio to your tolerance.
• Web research context. Optionally, the AI researches market context alongside your data. "Meta CPMs spiked 30% — likely due to Prime Day competition across the platform."
• Custom business context. Tell the trigger what matters to your business. "We're running a flash sale this weekend" or "Q4 is our peak season." The AI factors it in.

A DTC brand set a smart trigger on their Meta prospecting campaigns at Medium sensitivity. Within the first week, the trigger detected a gradual 18% increase in CPA that hadn't crossed any fixed threshold. The early detection saved an estimated $4K in wasted spend before the trend became obvious in the dashboard.

When you know exactly what to watch for. Set precise conditions and get notified the moment they're met.

What you get:

• Absolute or relative thresholds. "Alert when CPA exceeds $25" or "Alert when ROAS drops more than 15% week-over-week." Both work.
• Multiple conditions. Combine up to several thresholds with AND logic. "CPA above $25 AND spend above $500/day" — so you don't get alerts on low-spend noise.
• Re-check frequency. After a trigger fires, control how soon it can fire again. Prevent alert fatigue from the same issue.
• Sub-target filtering. Monitor specific campaigns, ad sets, or accounts. Not everything. Just what matters.

Four methods work together. A single method produces noise. Four methods calibrated to your data produce signal.

The four methods:

• Spike detection (standard deviation). Catches sudden jumps or drops that exceed normal variance. Configurable sensitivity for how many standard deviations count as anomalous.
• Trend detection (moving average). Smooths out daily noise and identifies when the underlying trend shifts direction. Catches slow drifts that threshold alerts miss completely.
• Recent change tracking (exponential smoothing). Weights recent data heavier than historical. Picks up emerging patterns before they're statistically obvious in longer windows.
• Seasonal pattern monitoring (decomposition). Learns your weekly and monthly cycles. Separates expected seasonal movement from genuine anomalies. Supports both additive and multiplicative patterns.

Triggers are just the beginning. Build complete analysis workflows that execute when conditions are met.

What you get:

• Sequential analysis steps. First detect the anomaly, then analyze contributing factors, then generate a recommendation. Each step builds on the last.
• Agent-based processing. Each step uses a data analyst agent that can query your data, run calculations, and write analysis in plain language.
• Test before activation. Run any step individually to verify it produces useful output before the whole workflow goes live.
• Parallel execution. Steps without dependencies run simultaneously. Complex analysis finishes faster.

Results go where your team already works. No one needs to log into another tool.

What you get:

• Email. Formatted analysis with PDF attachment. Send to workspace members or external recipients.
• Slack. Post to any channel via webhook. Alerts show up where your team is already talking.
• Microsoft Teams. Same integration depth as Slack. Channel posting with formatted cards.
• Google Chat. Workspace Chat webhook integration for Google-native teams.
• Webhooks. Generic webhook support for custom integrations. Pipe alerts into your own systems.
• Output modes. Choose between full report format, concise signal format, or raw data for system consumption.

Monitor every client account in parallel. Set smart triggers at Medium sensitivity across all workspaces. When something shifts for any client, you know before they do. The alert lands in your Slack channel with context and a recommended action. Walk into every client call already knowing what happened.

Stop checking dashboards hoping to catch problems. Set threshold triggers on your critical KPIs and smart triggers on everything else. The system watches 24/7 so you don't have to. When your Meta CPA creeps up or your Shopify conversion rate drops, you'll know within hours — not at the end of the week when the damage is done.