Anticipate Monta charger failures with AI
Swiftask connects your Monta chargers to an AI dedicated to predictive maintenance. Detect anomalies before they turn into breakdowns.
Result:
Maximize your charging point uptime and drastically reduce technical intervention costs.
AI Agents
monta
Connector monta · Secure OAuth 2.0
Unplanned downtime hurts your fleet profitability
Reactive management of charging stations is expensive and frustrating. When a charger fails, you lose revenue, disappoint users, and multiply emergency technician visits.
Main negative impacts:
Service unavailability
Every hour of downtime is a direct revenue loss and a degradation of user experience.
High maintenance costs
Emergency (corrective) interventions cost up to 3x more than planned maintenance.
Complex alert management
The volume of alerts generated by a fleet of chargers can overwhelm technical teams, leading to diagnostic errors.
Swiftask turns your Monta charger data into predictive signals. Our AI agents analyze flows in real-time to identify early failure signs and trigger automated preventive actions.
BEFORE / AFTER
What changes with Swiftask
Traditional approach
You wait for a charger to display an error code. The user reports the outage, you create a ticket, a technician travels for diagnosis, waits for parts, then repairs. Meanwhile, the charger is out of service.
Swiftask + Monta maintenance
The AI agent detects a voltage or temperature anomaly. It automatically generates a preventive maintenance ticket in your management tool, alerts your team, and suggests the necessary parts before the actual failure.
Setting up your predictive strategy
1
STEP 1 : Connect your Monta account
Integrate your Monta chargers to Swiftask in a few clicks via our secure connector.
2
STEP 2 : Define monitoring thresholds
Configure the critical parameters to monitor (power, temperature, system errors).
3
STEP 3 : Create the analysis agent
The AI agent learns your chargers' normal behaviors and identifies abnormal drifts.
4
STEP 4 : Automate actions
Configure alerts or automated ticket triggers based on AI diagnostics.
Intelligent supervision features
Multidimensional analysis of charging data: usage frequency, voltage variations, session success rates, and system error logs.
- Target connector: The agent performs the right actions in monta based on event context.
- Automated actions: Continuous log analysis, contextual alert sending, automatic ticket creation, integrated technical pre-diagnosis, fleet health report.
- Native governance: All analyses are centralized in Swiftask for a comprehensive view of your infrastructure reliability.
Each action is contextualized and executed automatically at the right time.
Each Swiftask agent uses a dedicated identity (e.g. agent-monta@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.
Operational optimization of your fleet
Increased availability
Significant reduction in downtime through failure anticipation.
Cost control
Prioritization of interventions on chargers truly at risk.
Extended lifespan
Proactive maintenance prevents premature wear of electronic components.
Technical peace of mind
Your teams only handle alerts qualified by artificial intelligence.
Facilitated scalability
Manage a fleet of 10 or 1000 chargers with the same efficiency thanks to automation.
Data security and compliance
Swiftask applies enterprise-grade security standards for your monta automations.
- Secure Monta API: Exclusive use of Monta's official and secure access points.
- Full encryption: All diagnostic data is encrypted at rest and in transit.
- Audit and traceability: Full history of AI analyses and triggered actions.
- Access isolation: Granular access control for your technical teams and contractors.
To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.
RESULTS
Measurable impact on your maintenance
| Metric | Before | After |
|---|---|---|
| Mean Time To Repair (MTTR) | 48-72 hours | Under 12 hours |
| Availability rate | 92% | 98%+ |
| Maintenance cost | Reactive (high) | Preventive (optimized) |
| Noise alerts | High volume | Filtered by AI |
Take action with monta
Maximize your charging point uptime and drastically reduce technical intervention costs.