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Mobility

AI for Mobility

AI delivers autonomy to cars and other modes of transport to reduce accidents and enable new business models, such as intelligent urban planning and autonomous deliveries. LatticeFlow enables ML teams to deliver performant AI models for mobility use cases while ensuring safety and robustness based on the latest standards.
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Use cases

autonomous driving
Autonomous Driving
autonomous rail transport
Autonomous Rail Transport
autonomous drone flight
Drone Flight
CASE STUDY

Smart City Analytics

Univrses used LatticeFlow to create performant AI models within few days, by auto-diagnosing the model and improving it with synthetic data, saving months of manual work for data curation and labeling.

<2 weeks

Time to adapt the AI model to a new domain
Saving months of labeling and engineering effort per deployment.

10+

Blind spots found and fixed
Observed in new deployments.

up to 3x

mAP improvement
On deployments in new domains.
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CASE STUDY
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Safety assessment of traffic sign detectors

The German Federal Office for Information Security used LatticeFlow to assess the safety and robustness of state-of-the-art traffic sign detectors.
Automatically Found Failures

30+

Robustness specifications defined
Covering camera noise, sign stickers, shadows, and others.

10+

Unknown failure modes uncovered
Confirmed with real-world images on which the model systematically fails.

70%

Certified robustness
While improving model accuracy by 0.2%.
Would you like to know more about this case study?
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Try LatticeFlow in action

Interested in trying LatticeFlow on your models? Curious to see how unknown blind spots can be easily found within minutes? Select one or more datasets and schedule a live demo to see our platform in action.
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