Enabling Contextual AI with Egocentric Data
Ramblr's data pipeline uses AI to enhance video data with expert knowledge. It improves your models by adding real-world context. Check out our demo or contact us for more info.
What we offer
Access to expert knowledge for everyone, everywhere, and all at once
Streamline your data-centric processes with our AI-powered pipeline. Enhance your data with expert insights and curate training datasets for MLLMs and Specialist AI assistants. From data collection to model deployment, we’ve got you covered. Contact us to get started!
Extract expert knowledge
Utilize your video data, either existing or collected with Ramblr, to extract on-the-ground process insights. Optimize your workflows, build a knowledge base of domain-specific processes, and train Specialist AI assistants to support your teams with the extracted expert knowledge.
Data Collection
Capture real-world process insights with secure egocentric data collection: We manage, organize and deliver your data collection project to your specs.
Data Privacy
We ensure privacy and security throughout the data lifecycle, whether you bring existing data or collaborate with us on egocentric data collection, through secure storage and processing. You can trust that we handle personally identifiable information (PII) with care at every step.
Organize and Structure Datasets
Seamlessly enhance videos with expert knowledge using video intelligence. Efficiently manage large video datasets for data insights and downstream tasks.
Annotate Videos
Harness the power of AI-guided automated annotations to enrich your data. Create a foundational data framework to fine-tune your MLLM and Specialist AI models to your specific domain and use-cases.
Fine-tune MLLMs
Automatically generate instruction-tuning datasets grounded in video context and annotations. Fine-tune generic MLLMs with your proprietary domain-specific data.
Train Specialist AIs
Enhance your AI solutions by fine-tuning pre-trained VLMs with your proprietary domain-specific data. Customize Specialist AI models, unlocking expert knowledge within your data.
Specialist AIs can solve the one screw left problem…
Current AIs lack information for real-world, task-specific solutions. Customize LLMs with multimodal data and using Q&A pairs from Ramblr to accomplish specialized tasks. Specialist AIs can solve the one screw left problem.
Discover how a Specialist AI assistant can learn to solve the one-screw left problem using Ramblr's AI-assisted data pipeline.
Keyframe Identification
Ramblr’s AI identifies keyframes in videos, streamlining annotation with automation. The masks from annotated keyframes can be propagated across the entire video.
Mask Propagation
Annotations are propagated across frames. Dozens, if not hundreds, of individual frames can be propagated from a single annotated keyframe.
Anomaly Detection
Our AI detects and corrects anomalies with minimal human intervention. If an anomaly spans multiple frames, we automatically select the best frame to correct the anomaly and propagate it to adjacent frames.
Global ID Matching
Objects are consistently annotated throughout the video, even as they move in and out of the scene. This enables AI assistants to understand videos as a whole.
Work with us
Try it out in the Demo Environment
Sign-up to discover our tools and experience our automated annotation pipeline and R.PRO demos. Contact us to discuss your needs, or schedule a deep dive with us.
Scale Up your Projects.
Ramblr's infrastructure and tools adapt to your data requirements. Collaborate with your team on large video datasets or enlist our expert annotators, we ensure seamless scalability. Our task management system orchestrates AI processes, human annotation, and validation tasks for optimal project efficiency.
Track progress in the project dashboard.
Manage your projects on the individual task level.
What's new
Annotation KPIs Benchmark Study
The outcome of our benchmark study: annotating 1 hour of open-world Egocentric Video in just 157 hours. With 97% of 109,370 frames automatically annotated, the average time per frame is 5.2 seconds. Quality metrics demonstrate an impressive 0.94 IOU and a 0.90 F1 score.
Instruction-tuning One Pager
Supercharge your models’ reasoning and factual accuracy with custom instruction-tuning datasets. Ramblr’s advanced video annotations provide multimodal LLMs with precise contextual, spatial, and temporal understanding.
We're Global
Join our team of Data Scientists, ML-Engineers, Software Developers, and UX Designers to shape the next wave of Contextual AI.
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