Ramblr provides an end-to-end platform for training and deploying enterprise AI Agents using real-world data. The system transforms unstructured multimodal data from devices like AR/MR headsets and robotics into structured datasets for AI model training. This enables the deployment of AI Agents to assist human operators, automate workflows, and enhance decision-making in physical operations.
Funding
$0 raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Training AI agents to understand and interact with the physical world requires processing vast amounts of multimodal video data, which is traditionally a manual, time-consuming, and expensive process. Existing video annotation platforms often lack the automation, scalability, and precision needed to handle complex industrial use cases. This creates a bottleneck in deploying AI solutions for tasks such as quality control, process monitoring, and robotic automation.
Solution
Ramblr provides an end-to-end platform, the Ramblr Data Engine, for training and deploying multimodal AI agents that can understand and interact with the physical world. The platform streamlines the process of capturing, segmenting, and annotating video data, enabling the creation of high-quality datasets for training AI models. Ramblr's AI agents can then be deployed to AR/MR devices, mobile devices, robotic systems, and cloud applications to assist with task execution, automate repetitive workflows, and enhance efficiency in real-world operations. The platform supports leading foundation models and offers features such as automated object tracking, activity captioning, and scene graph generation.
Target Audience
Ramblr's primary customers are enterprises in industries such as manufacturing, agriculture, and construction who are looking to deploy AI agents to automate tasks, improve quality control, and enhance operational efficiency.
Features
- End-to-end platform for training, deploying, and optimizing multimodal AI agents
- Support for various data modalities including video, audio, text, and sensor data
- Automated video annotation with features like instance segmentation masks and consistent object tracking
- Generation of activity captions, scene graphs, and instruction-tuning pairs
- Integration with leading AI foundation models such as GPT-4o, Gemini, Azure GPT, and NVIDIA NIM
- Deployment options for AR/MR devices (Android XR, visionOS, Horizon OS), mobile devices (Android, iOS, ARCore, ARKit), robotic systems (NVIDIA GR00T-Perception), and cloud applications (Azure, Google Cloud)
- Tools for managing projects, browsing datasets, and collaborating with teams
- Scalable infrastructure designed to handle demanding video workloads