Robotics
Accurately label and curate physical AI data to supercharge robotics
Discover and label millions of images and videos of complex static or dynamic scenarios with pixel-perfect precision using AI-assisted annotation and human reviews to train and fine-tune Physical AI models.
Download Robotic's E-Book
The rise of intelligent machines
The future of physical AI is being built with Encord
The fastest way to curate and annotate relevant AI data
Securely discover, curate, and visualize relevant computer vision, audio, and text data across AWS, GCP, and Azure.
Fine-grained AI-assisted labeling and reviews to ensure extreme accuracy for tasks-specific context.
Continuous improvement cycle to evaluate and validate AI model predictions and curate the most valuable data for model fine-tuning.
Powering every Physical AI use case for Robotics
Transform petabytes of raw data into proprietary AI ready data to gain new competitive advantages. Curate and annotate multimodal data to effectively train and fine tune Physical AI models powering your machines.
Warehouse & logistics
Healthcare
Intelligent manufacturing
Agriculture technology
Construction
Autonomous vehicles
Testimonial
What our Robotics customers say
Mira Murali
Computer Vision Engineer at Four Growers
“The fact that Encord was able to offer both an automatic labeling tool as well as a team of annotators that we could use was very attractive. We need that flexibility...Using Encord has more than halved the time it takes us to provide feedback on imagery. What could have previously taken us 2 hours now takes approximately 30 minutes."
Curate diverse datasets to handle the unpredictability of real-world environments
Reduce model bias with under-represented data
Explore billions of video frames with granular filtering, sort, and search using quality metrics, custom metadata, natural language queries, and embedding plots.
Curate millions of video files using quality metrics
Explore videos temporally using embeddings-based quality metrics to find the most valuable data, including hard-to-find edge cases, for labeling and creating diverse datasets for model training and fine-tuning.
Train and fine-tune Physical AI models with accurately labeled data to improve navigation in complex environments
Render and annotate videos natively to eliminate frame splitting and synchronization issues
Validate and correct Physical AI-powered robot operations with RLHF
Label multiple views of the same scenario in one interface to improve adaptive behavior
Combine visual, audial, and text data for improved environment and hazard understanding
Boost labeling accuracy and speed with Meta’s SAM 2 and HITL for AI-assisted annotation
Forget fragmented workflows, annotation tools, and Notebooks for building AI applications. Encord's Data Development platform accelerates every step of taking your model into production.
