With Ramblr 1.0, we enable companies and academic institutions to collect, segment, and annotate large multi-sensor datasets in a cost-efficient way. Our scalable and privacy-preserving platform as well as our efficient AI-Guided user-interface helps annotators, data scientists, and application developers deploy Augmented Reality applications faster.
egocentric data is complex
It is unique in its challenges, difficult to collect, expensive to label, and complex to manage
Unlimited Diversity of Use Cases
Supporting you to define AR use cases, determine data needs, and develop a collection plan.
Distributed Data Collection
Collection of high-quality, multi-sensory, real-world data — let's work together to collect diverse egocentric datasets of daily-life activities from around the world.
Legal compliance system and data privacy framework to satisfy local regulations and support responsible data practices.
AI-Based Long-Video Annotation
Cost-efficient panoptic segmentation of long video sequences leveraging ramblr's proprietary AI models. Integrated in our cloud-native deep learning architecture with purpose-built tools.
Model Performance & Data Quality
Semi-automated QA to detect biases, corner cases, and class imbalances and to re-evaluate data collection needs based on model performance.