Detect energy consumption anomalies using Corrently data
Swiftask connects your Corrently data to an analytical AI. Instantly identify abnormal consumption spikes and hidden inefficiencies.
Result:
Anticipate energy overspending and ensure infrastructure stability with proactive AI-driven monitoring.
AI Agents
corrently
Connector corrently · Secure OAuth 2.0
Complex energy data hides critical inefficiencies
Monitoring energy consumption manually is impossible given the volume of data generated. Anomalies go unnoticed until bills arrive, leading to financial losses and avoidable environmental impact.
Main negative impacts:
Hidden operational costs
Energy leaks or faulty equipment consume resources unnecessarily until late detection during billing cycles.
Critical equipment failures
Consumption anomalies are often early warning signs of major hardware failure in your installations.
Lack of analytical visibility
Standard tools provide raw data but fail to correlate events to identify the root causes of overconsumption.
Swiftask integrates Corrently flows to apply AI models capable of detecting energy behavior deviations in real time, alerting you as soon as an anomaly is identified.
BEFORE / AFTER
What changes with Swiftask
Reactive data management
You review weekly or monthly reports on Corrently. Anomalies are discovered after the fact, preventing quick corrective action and maximizing losses.
Swiftask intelligent monitoring
As soon as consumption deviates from established norms, Swiftask AI triggers an immediate alert with contextual analysis, enabling instant technical intervention.
Setting up your anomaly detection in 4 steps
1
STEP 1 : Connect your Corrently data
Link your Corrently account to the Swiftask platform to securely import your energy data flows.
2
STEP 2 : Define baseline thresholds
Configure the AI agent with your normal consumption parameters to establish a solid baseline.
3
STEP 3 : Configure the analysis engine
Activate anomaly detection algorithms to monitor temporal variations and consumption spikes.
4
STEP 4 : Setup alert channels
Determine where you want to receive anomaly notifications for optimal responsiveness.
Your energy agent's analytical capabilities
The AI analyzes historical trends, seasonality, and external correlations to isolate real anomalies from normal fluctuations.
- Target connector: The agent performs the right actions in corrently based on event context.
- Automated actions: Automatic threshold breach alerts. Trend analysis for predictive maintenance. Automatically generated anomaly reports. Multi-flow integration for cross-comparison.
- Native governance: Swiftask ensures full logging of every detection to facilitate your energy audits.
Each action is contextualized and executed automatically at the right time.
Each Swiftask agent uses a dedicated identity (e.g. agent-corrently@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.
Why choose Swiftask for Corrently data
Energy cost reduction
Identify and eliminate energy waste before it affects your bottom line.
Simplified predictive maintenance
Detect signs of equipment fatigue through analysis of their energy signature.
Compliance and reporting
Automatically generate compliance reports based on data analyzed by Swiftask.
Automation without AI expertise
Benefit from machine learning power without needing an in-house data science team.
Scalable monitoring
Monitor an unlimited number of measurement points with the same precision, regardless of fleet size.
Security and data integrity
Swiftask applies enterprise-grade security standards for your corrently automations.
- Flow encryption: All data moving between Corrently and Swiftask is encrypted according to banking standards.
- GDPR compliance: Strictly compliant management of consumption data, respecting privacy and regulations.
- Granular access control: Fine-tuned access management within Swiftask to ensure only authorized personnel see alerts.
- Technological independence: Flexible architecture allowing total interoperability with your other infrastructure management tools.
To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.
RESULTS
Energy monitoring performance
| Metric | Before | After |
|---|---|---|
| Anomaly detection | Several days (human) | Real-time (AI) |
| Alert accuracy | High false positive rate | Context-trained models |
| Maintenance cost | Expensive emergency repairs | Targeted preventive intervention |
| Global visibility | Data silos | Unified dashboard |
Take action with corrently
Anticipate energy overspending and ensure infrastructure stability with proactive AI-driven monitoring.