Use data to optimise micromobility operations, reduce costs and increase revenue.
We make micromobility companies more profitable through demand predictions and route optimisation.
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Boost rides by up to 30 %
With Lanterne you get
- 30 % more rides on fleet level and
- more than double the rides per vehicle per day after a rebalancing intervention.
Know demand patterns ahead of time
We provide you with detailed demand predictions to facilitate smart mobility. You’ll know exactly when and where you should be distributing micromobility vehicles to increase the number of rides per day. With Lanterne you get demand predictions:
- through an API, dashboard or emails – tailored to suit your operations
- on an hour-by-hour basis
- down to the street-level
Get the most valuable tasks done
Our smart tasks solution prioritises the highest impact battery swapping and rebalancing tasks. Get your fleet ready to capture as much demand as possible.
Reduce cost per task
Our innovative route optimisation system will help you to get all your highest value tasks done in the most efficient way possible.
We distribute tasks efficiently between your operations vehicles and dynamically optimise the route to increase task density and decrease your operations costs.
How it works
We ingest your utilisation data and combine it with external data to train our demand prediction model. We then use the state of your fleet, and the demand predictions to create and prioritise operations tasks.
A route optimisation system then helps you to get the most valuable tasks done in the most efficient way possible.
Our solution is easy to integrate
The operator provides access to their rides and supply data feed (e. g. a MDS feed).
Lanterne generates demand predictions and actionable fleet optimisation recommendations.
The operator receives predictions and recommendations through our dashboard or an API.
The operator rebalances the fleet to close the demand-supply gap.
Lanterne's Covid-19 response
Lanterne developed Crowdless, a free platform with global coverage that helps people with social distancing. It provides real-time data on how crowded supermarkets are so that people can avoid crowds, choose the least busy place and best time to visit. The platform uses a combination of existing data sources and crowdsourced data in combination with machine learning.
