Swiftask turns your Control D filtering logs into actionable notifications. Get alerted instantly on anomalies and threats, without the noise.
Result:
Save valuable time by filtering out the noise and focusing only on real threats to your infrastructure.
AI Agents
control d
Connector control d · Secure OAuth 2.0
Control D generates a massive amount of filtering data. Without an intelligent alerting system, your security teams spend their time sorting through logs instead of neutralizing real threats. The result: alert fatigue and missed critical incidents.
Main negative impacts:
Alert fatigue
The volume of unfiltered notifications leads to desensitization. Critical alerts are buried in the noise.
Slow reaction time
Time spent manually analyzing logs delays the implementation of corrective measures on your network.
Lack of context
A single log is not enough. Without correlation, it's impossible to understand the severity of a blocked access attempt.
Swiftask connects your Control D data to an AI engine that analyzes, filters, and prioritizes your alerts in real-time, notifying you only about critical events.
BEFORE / AFTER
Manual log management
Your team receives thousands of raw logs daily. They must manually extract suspicious patterns, check IPs, and decide whether to act. Meanwhile, the attack continues.
Smart Alerting with Swiftask
Swiftask monitors Control D. As soon as suspicious behavior is detected, the AI agent analyzes the context and sends a summarized, prioritized alert directly to your team via Slack, Teams, or Email.
1
STEP 1 : Link your Control D account
Connect Control D to Swiftask via API to allow secure ingestion of your DNS filtering logs.
2
STEP 2 : Define your criticality rules
Configure the thresholds and patterns that should trigger a smart alert (e.g., repeated access to malicious domains).
3
STEP 3 : Configure alert routing
Determine which channels (Teams, Slack, PagerDuty) receive alerts based on their priority level.
4
STEP 4 : Automate responses
Enable automatic actions (e.g., temporary IP blocking) following an AI-validated alert.
The AI analyzes volume, frequency, domain reputation, and access history to qualify each alert.
Each action is contextualized and executed automatically at the right time.
Each Swiftask agent uses a dedicated identity (e.g. agent-control-d@swiftask.ai ). You keep full visibility on every action and every sent message.
Key takeaway: The agent automates repetitive decisions and leaves high-value actions to your teams.
Eliminate 90% of false alerts thanks to Swiftask's contextual analysis.
Identify and neutralize threats before they impact your network infrastructure.
Free your engineers from manual monitoring tasks for high-value projects.
Centralize alerts from all your security tools in a single interface.
Keep an immutable trail of every alert and action taken.
Swiftask applies enterprise-grade security standards for your control d automations.
To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.
RESULTS
| Metric | Before | After |
|---|---|---|
| Noise alerts | 80% of daily volume | Less than 5% after filtering |
| Detection time | Several hours | Less than 30 seconds |
| Incident response | Manual and slow | AI-automated |
| Team overload | High (burnout) | Optimized and focused |
Save valuable time by filtering out the noise and focusing only on real threats to your infrastructure.