Enabling Contextual AI with Egocentric Data
Efficient multi-sensor video annotation
Ramblr's scalable AI-powered pipeline and tools generate high-quality multi-sensor training data. We leverage state-of-the-art Machine Learning models to automate video annotation with human feedback.
97%
Increase annotation efficiency with AI-assisted tools.
What we Offer
Work with us to define your data needs and the areas of improvement for your ML model.
Ramblr will collect and annotate your data and work hand-in-hand with you to evaluate, improve, and launch your models into production.
Data Collection
Privacy-preserving, secure data collection of high-quality egocentric data. We manage, organize, and deliver your data collection project according to your requirements.
Data Annotation
Scalable AI-powered video annotation to generate accurate and consistent instance segmentation masks in accordance with your specifications.
Data Browser
Cloud-native infrastructure to manage, curate, and validate large datasets in preparation for the training of your Machine Learning models.
Data Privacy
Data protection and privacy from collection to ingestion to the removal of personally identifiable information (PII) right through to data storage and transfer.
Our Technology
Ramblr’s AI-assisted video annotation process is the fastest way to generate training data for AR/MR, Contextual AI, and Robotics.
Ramblr’s data engine generates consistent spatiotemporal segmentation masks and semantic labels for all context relevant objects.
Multi-modal Data Collection
We support various sensor sources. Sensor data includes RGB and monochrome cameras along with IMU, audio, eye tracking and more. Recorded data, metadata, and sensor streams can be accessed with Ramblr’s data browser. We are agnostic to data collection devices, so bring your own or ask us for recommendations.
AI-guided Video Annotation
Browser-based and purpose-built to efficiently annotate egocentric video data. We use state-of-the-art ML models and egocentric data specific signals to detect and track context-relevant objects of interest in the video and for AI-assisted annotation. We identify representative keyframes and propagate the segmentation masks and semantic labels throughout the video, reducing annotation time significantly.
Automated QA Process
To ensure consistent and high-quality annotations throughout the video, our quality assurance (QA) model automatically detects category inconsistencies, object mask shape anomalies, and missing object masks. The system tracks objects across all frames using globally unique object identifiers while also tracking reoccurring objects and detecting new, relevant objects. Human annotators correct the detected issues, and we propagate the corrected masks, reducing annotation efforts without sacrificing accuracy.
Data Browser
Gain insights, manage, explore, and search your datasets. Curate and validate your high-quality annotated data and access relevant metadata. With Ramblr’s data browser you can speed up your data-centric processes and visualize the high-quality data that production-ready models need.
We're Global
Join our team of Data Scientists, ML-Engineers, Software Developers, and UX Designers to shape the next wave of Contextual AI.
Take a Look
Multi-sensor Data for Egocentric AI
Data captured from a first-person view (aka “egocentric data”) enables a multitude of Augmented Reality applications. Collecting, processing, segmenting, and annotating egocentric data poses unique challenges, including the handling of large datasets capturing a wide variety of use cases. At Ramblr, we are building a full service egocentric data pipeline and AI-assisted tools to address the unique challenges of Egocentric AI.
Ramblr 1.0 - Enabling AI systems to see the world like humans do.
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-assisted tools help annotators, data scientists, and application developers to deploy Augmented Reality applications faster.
Stay Up-to-Date
Contact us to discover upcoming product improvements and releases.
3.2 sec
The amount of time it takes to subscribe to our newsletter.