How AI is optimising the charging of private vehicles and electric fleets in Colombia

Electric vehicle (EV) adoption in Colombia is on the rise: according to the National Association for Sustainable Mobility (ANDEMOS), sales reached 33,921 units, while diesel vehicles totalled 16,960.

However, electric fleets still face technical, regulatory, and financial challenges that hinder charging infrastructure development.

In this context, two local startups, Ergenia and EV Predictor, are harnessing artificial intelligence to bridge the gap and improve the operational efficiency of charging systems.

While EV Predictor operates as a predictive tool that helps users plan their journeys, Ergenia functions as a charge point operator that integrates hardware, software, and maintenance services to optimise the charging experience.

The integration of AI in charging management is essential for fleet operation, as it enables:

• Reduction of downtime
• Prevention of overloads
• Distribution of demand during optimal time slots

For last-mile or urban transport operators, every kilowatt saved can represent a competitive advantage and a direct improvement in operational efficiency.

Data, Efficiency and Forecasting: Ergenia’s Proposition

Ergenia is a Colombian company founded by Argentine entrepreneur Vicente Lanza.

Its business model combines the installation of charging stations, 24/7 operation, and a technology layer that uses artificial intelligence to monitor demand, automate processes, and generate predictions.

“Our tech platform allows us to forecast demand, monitor in real time, and offer automated recommendations for efficient energy use,” explains Lanza in a conversation with Mobility Portal Latin America.

The AI developed by Ergenia tracks real-time charging and energy consumption habits of each connected unit.

Using this data, the system can prioritise charging, generate efficiency alerts, and recommend strategic locations for new stations.

The company operates with a dual focus: public charging (B2C) and fleet charging (B2B), including taxis, last-mile vehicles, and logistics operators.

In both cases, the AI draws on user behaviour data, vehicle specifications, and energy usage to improve decision-making.

Through this, Ergenia can determine the kilowatt consumption of each unit, link it to vehicle registration, and provide fleet management tools to boost productivity.

“AI enables us to improve efficiency and productivity for the businesses that hire us,” Lanza adds.

Ergenia began operations in Bogotá and plans to close 2025 with 8 to 10 public charging stations installed, in addition to private projects. Its expansion roadmap includes scaling to Medellín and reaching 80 stations across Colombia within five years.

According to Lanza, the model is designed to be replicable in other Latin American countries and can serve both fleet and individual users.

Topography, Planning and Simulation: EV Predictor’s Approach

Founded in 2022 by Colombian geophysicist Julián Escallón, EV Predictor was born out of the need to understand EV energy performance on complex routes, particularly in a mountainous country like Colombia.

“People are afraid to take their EVs on the road—and rightly so. On the outbound trip you might use 10% of the battery, but on the return leg 80%. A miscalculation can be costly,” Escallón explains.

The EV Predictor app models each vehicle’s energy consumption by combining three variables: vehicle performance, battery response, and route topography.

Its data infrastructure includes detailed information on frequent routes, elevation profiles, and energy use.

The system allows for simulations of routes such as Bogotá–Melgar, anticipating the kilowatt requirements for each segment of the journey.

“The platform is designed to help users plan their mobility. Driving an EV isn’t like a combustion vehicle—it’s about optimising time and charge points,” says Escallón.

Their business model is subscription-based, offering monthly, semi-annual, or annual plans, targeting both private users and fleet managers.

Additionally, the company is independently mapping and updating Colombia’s network of charging stations due to the lack of reliable official data.

“The government’s platform was meant to show all charging points, but it lists fewer than 10% of those actually in operation. We have to verify them one by one,” Escallón explains.

The app compiles data from ElectroMaps, PlugShare, and user reports, alongside direct searches of hotels, fuel stations, and social media.

The system is built on a proprietary mathematical model using applied physics and altimetry data from Colombian routes.

It simulates journeys based on vehicle make, battery type, and specific route topography.

“We don’t use generic models—we adjust them based on real-world tests and academic research,” Escallón clarifies.

Electric Fleets and Smart Charging Planning

Both companies identify electric fleets as strategic users in the transition to e-mobility.

AI makes it possible to monitor key metrics such as:

• Energy consumption per unit
• Efficiency per journey
• Optimal charging schedules
• Maintenance control

From Ergenia, Lanza highlights the immediate value this brings: “A fleet can know how many kilowatts each vehicle charged, how much it earned, and what its efficiency was. All of that directly impacts operating costs.”

EV Predictor, meanwhile, works with urban charge point operators and transport firms to model optimal routes.

“The key is good planning—knowing how much to charge, where, and when. That changes the logic of transport,” Escallón says.

Both startups see intelligent planning as a key factor in advancing toward more rational mobility, especially in environments where infrastructure is still limited or unevenly distributed.

Colombia: Electric Vehicle Progress in Pause

Colombia has one of the highest rates of EV penetration in Latin America.

It offers tax incentives (such as a reduced 5% VAT) and logistical benefits (parking, insurance, tax reductions). However, charging infrastructure deployment is increasingly uneven.

There are currently between 400 and 450 charging stations, with only about 70% being fast-charging. Most are concentrated in Bogotá, Medellín, and urban shopping centres. Intercity coverage remains limited.

“In December, queues of up to six cars per station were common. Today, many are underused. Infrastructure is insufficient during peak demand and idle during off-peak times,” says Escallón.

From the perspectives of both Ergenia and EV Predictor, the key lies in developing sustainable, scalable models supported by intelligent technologies.

“Electric mobility requires planning. We’re here to help drive that mindset shift,” concludes Escallón.

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