Swiftask connects your AI agents to your Monta infrastructure. Dynamically adjust charging power in real-time to balance your energy consumption.
Result:
Cut energy bills and extend equipment lifespan while ensuring maximum availability for your users.
AI Agents
monta
Connector monta · Secure OAuth 2.0
Managing multiple charging stations without automation leads to costly consumption spikes and local power grid overload risks. Without intelligent control, you face high energy costs and inefficient power distribution.
Main negative impacts:
Expensive demand peaks
Simultaneous charging at full power significantly inflates your energy bills and can trigger grid penalties.
Local overload risk
Without dynamic load balancing, you risk exceeding your site's electrical capacity, leading to unexpected power trips.
Lack of operational agility
Manually adjusting current limits for each charger based on site occupancy is slow and prone to human error.
Swiftask automates load management for your Monta chargers. Through intelligent rules, the agent adjusts available power based on building consumption, time-of-use tariffs, or charging priorities.
BEFORE / AFTER
Traditional management
Your chargers run at full power as soon as a vehicle is plugged in, ignoring the building's overall consumption. This leads to exceeded power limits and unoptimized energy costs.
Swiftask + Monta smart control
Your AI agent monitors real-time site consumption via your monitoring systems. It sends dynamic adjustment commands to Monta chargers to smooth the load curve and prioritize off-peak hours.
1
STEP 1 : Connect your Monta account
Securely integrate your Monta chargers with Swiftask via API. Set up access to enable dynamic charging parameter adjustments.
2
STEP 2 : Define your control rules
Establish power thresholds, tariff-based time slots, or business-driven priorities within the no-code interface.
3
STEP 3 : Configure intelligent triggers
The AI agent activates based on your consumption sensors, dynamic energy prices, or specific alerts on your electrical network.
4
STEP 4 : Monitor and refine
Track charging performance on the Swiftask dashboard. Adjust your rules as your charging station fleet evolves.
The AI agent continuously analyzes consumption data, real-time energy prices, and Monta charger status to calculate optimal power output.
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.
Avoid consumption peaks and leverage lower rates through AI-driven automated control.
Prevent electrical overloads by matching charging power to available site capacity.
Maintain a log of every adjustment, simplifying environmental and energy reporting requirements.
Adapt your charging strategies without writing a single line of code, directly within Swiftask.
Add new Monta chargers to your ecosystem without changing your global management rules.
Swiftask applies enterprise-grade security standards for your monta automations.
To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.
RESULTS
| Metric | Before | After |
|---|---|---|
| Energy costs | Standard (peak pricing) | Optimized (-15% to -30% estimated) |
| Overload risk | High (manual) | None (AI-automated) |
| Charger management | Manual and reactive | Proactive and autonomous |
| Implementation | Complex development | Quick no-code setup |
Cut energy bills and extend equipment lifespan while ensuring maximum availability for your users.