Pricing

Predictive maintenance: anticipate solar performance with Solcast

Swiftask correlates Solcast weather data with your sensor readings to predict production drops. Act before the failure happens.

Result:

Maximize uptime and drastically reduce corrective maintenance costs.

Reactive maintenance is bleeding your solar assets

Waiting until a production drop is observed to intervene is a costly strategy. Emergency interventions are unpredictable, require expensive logistics, and generate direct revenue losses during downtime.

Main negative impacts:

Unanticipated revenue losses: Every hour of unplanned downtime is lost money. Lack of prediction prevents quick reaction.
High logistical costs: Emergency interventions mobilize specialized technicians at the last minute, increasing travel and labor costs.
Accelerated equipment wear: Lack of preventive maintenance based on real conditions reduces the lifespan of inverters and panels.

Swiftask continuously analyzes Solcast forecasts and your operational data to trigger targeted maintenance alerts. You intervene only when necessary, at the best possible time.

BEFORE / AFTER

What changes with Swiftask

Traditional approach

Yield drops. The technical team is alerted by a system alarm, often too late. An on-site inspection is scheduled, diagnosis takes time, and spare parts are not immediately available.

Swiftask + Solcast approach

The AI detects a performance anomaly compared to Solcast irradiance forecasts. An alert is generated, diagnosis is pre-established, and the intervention is planned during a predicted low-sunlight period.

Deploy your predictive strategy in 4 steps

STEP 1 : Integrate Solcast feeds

Connect your Solcast API key to Swiftask to ingest real-time irradiance and temperature forecasts.

STEP 2 : Configure AI models

Define expected performance thresholds based on weather data. The agent learns your installation's normal behavior.

STEP 3 : Automate alerts

Configure intelligent notifications to your CMMS or technical teams as soon as a deviation is detected.

STEP 4 : Continuous analysis and optimization

Refine models with real intervention reports to improve maintenance accuracy over time.

Predictive analysis capabilities

The agent correlates irradiance predicted by Solcast with actual production to identify abnormal drops due to soiling, electrical faults, or shading.

Target connector: The agent performs the right actions in solcast based on event context.
Automated actions: Automatic alert on performance deviation. Intelligent intervention scheduling. Diagnostic report generation. Integration with maintenance management systems via webhooks.
Native governance: Alerts are contextual: they consider past and future weather to avoid false positives.

Each action is contextualized and executed automatically at the right time.

Each Swiftask agent uses a dedicated identity (e.g. agent-solcast@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.

Major operational benefits

1. Reduced downtime

Intervene before major failure through early anomaly detection.

2. Optimized field costs

Schedule technician routes based on weather forecasts to maximize their efficiency.

3. Increased energy yield

Maintain your installations at their nominal performance level with responsive monitoring.

4. Data governance

Centralize performance and intervention history for better traceability.

5. No-code flexibility

Adapt your predictive models without data science knowledge.

Security and data reliability

Swiftask applies enterprise-grade security standards for your solcast automations.

Encrypted API access: Your Solcast keys and production data are processed via secure connections.
Environment isolation: Each client benefits from an isolated Swiftask environment for maintenance data.
Compliance and audit: Every alert and action is logged for your regulatory compliance needs.
Model sovereignty: You keep full control over the rules and thresholds applied by your agent.

To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.

RESULTS

Impact on your key metrics

Metric	Before	After
Asset uptime	85-90%	98%+
Average intervention cost	High (emergency)	Optimized (planned)
Anomaly detection	Reactive	Proactive (predictive)
Diagnosis time	Several hours	A few minutes (AI assisted)

Take action with solcast

Maximize uptime and drastically reduce corrective maintenance costs.

Centralize Solcast data automatically with your AI agents

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