Best Alternatives to Pegasus 1.6 by TwelveLabs in 2025
Pegasus 1.6 by TwelveLabs is a specialized video understanding model that transforms egocentric and teleoperated video into structured, timestamped metadata for robot training. It excels at analyzing first-person footage to recognize entities and produce persistent labels across segments, enabling robotics and physical AI teams to generate training data without manual annotation. However, depending on your specific needs—such as budget, deployment flexibility, or additional modalities—other tools may be better suited. Here are the best alternatives to Pegasus 1.6.
Roboflow
Roboflow is a comprehensive computer vision platform that supports video annotation, model training, and deployment. It offers tools for labeling video frames, managing datasets, and training custom models, making it a strong alternative for teams that need end-to-end video data pipelines for robotics. While it doesn't specialize in egocentric video understanding out-of-the-box, its flexibility and active community make it a popular choice.
Scale AI
Scale AI provides data labeling and annotation services for video, including sensor fusion and 3D data. For robotics teams, Scale offers managed labeling workforces and quality control, which can be more scalable than in-house annotation. It's a good alternative if you need high-quality, human-in-the-loop labeling for robot training data, though it may be more expensive than automated solutions.
Labelbox
Labelbox is a data labeling platform that supports video annotation with features like frame-by-frame labeling, object tracking, and ontology management. It integrates with machine learning pipelines and offers both manual and automated labeling. For robotics teams, Labelbox can handle egocentric video data and produce structured metadata, but it requires more setup than a specialized model like Pegasus 1.6.
Supervisely
Supervisely is an end-to-end computer vision platform that includes video annotation, model training, and deployment. It supports custom neural network architectures and offers tools for tracking and segmentation in video. It's a viable alternative for teams that want to build custom video understanding models for robotics, though it may lack the specific egocentric video optimizations of Pegasus 1.6.
V7 Labs
V7 Labs provides a video annotation and model training platform with AI-assisted labeling. It supports object tracking, action recognition, and custom workflows. For robotics, V7 can help create training datasets from egocentric video, but it's more of a general-purpose tool and may not offer the same out-of-the-box understanding of teleoperated footage as Pegasus 1.6.
Clarifai
Clarifai offers a video recognition API that can detect objects, actions, and scenes in video streams. It's a cloud-based solution that can be used for robotics applications, but it may not provide the persistent metadata and segment-level understanding that Pegasus 1.6 specializes in. It's a good option for teams that need general video understanding without building custom models.
AWS Rekognition Video
Amazon Rekognition Video is a managed service that analyzes video for objects, faces, activities, and more. It can process stored or streaming video and is integrated with AWS services. For robotics teams already on AWS, it's a convenient alternative, but it's not tailored for egocentric or teleoperated footage and may require additional processing to generate robot training data.
While Pegasus 1.6 by TwelveLabs offers specialized understanding of egocentric and teleoperated video for robot training, alternatives like Roboflow, Scale AI, and Labelbox provide broader data labeling and computer vision capabilities. The best choice depends on your need for automation, customization, budget, and integration with existing workflows. For teams seeking a turnkey solution for robot training data, Pegasus 1.6 remains a strong contender, but these alternatives are worth considering based on your specific requirements.