LiDAR

Build state-of-the-art Physical AI

Streamline multimodal AI data pipelines to accelerate robot perception, navigation, and manipulation capabilities for reliable operation in complex physical environments

The future of physical AI is being built with Encord

Train and fine-tune Physical AI models with accurately labeled data to improve navigation in complex environments

Vision Language Action (VLA)

Bridge natural language and robotic execution. Connect physical objects to language descriptions, powering foundation models that understand complex human commands.

Robot Vision

Powerful multimodal visual data support whether video, 3D, 6 DOF pose estimation, or other sensors to efficiently build products like warehouse AMRs, humanoid robots, quality inspection systems and more.

3D scene visualization for multimodal point cloud, video and sensor data

Master complex 3D scenes with all sensors unified on a timeline. From raw sensor data, point clouds from LiDAR, and multiple camera angles, you can manage, search, curate, label your data and test models with ease.

ADAS

Industrial

Healthcare

Defense

Agriculture

Visualize, curate and annotate 3D, LiDAR and point cloud data in one unified solution

Ingest and visualize sensor data

Stream high-volume, continuous raw sensor data including LiDAR point clouds, camera imagery, diverse telemetry in common industry formats like MCAP.

Annotate complex 3D, multi-sensor scenes

Cut annotation time with automated object tracking and single-shot labeling across scenes; and ensure consistent, precise labels across sensors that adapt as your requirements evolve.

Intelligent data curation and QC

Automated quality checks and edge case detection. Efficiently filter, batch, and select precise data segments for specific annotation and training needs.

Intuitive UI for RLHF and HITL review

Validate and correct model behaviour within a customizable multimodal interface. Set up flexible data workflows to ensure data quality at scale.

Automate any data task with Encord Agents

Integrate SOTA models or your own models directly into your data workflows to automate any data action such as reviews, pre-labeling, data classification, filtering and more.

Streamlined workflows and collaboration

Optimize operational efficiency by easily distributing tasks among annotators, tracking performance, assigning QA reviews, and ensuring compliance across projects.

Deploy production AI faster with leading AI teams

Join thousands of ML practitioners deploying production-ready AI applications with integrated data pipeline to optimize the data curation and annotation cycle.

30%

improvement in annotation accuracy

Read Pickle Robot’s story

40+

annotators trained using Encord

Read Tractable’s story

$600K

saved per year

Read Standard AI’s story

Identify edge-cases to improve perception systems in real-world conditions at scale

Curate millions of 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.

Reduce model bias with under-represented data

Explore billions of data points with granular filtering, sort, and search using quality metrics, custom metadata, natural language queries, and embedding plots.

Nick Gillian

Founder & Head of AI
Archetype

“Encord brought together scalability, video-native annotation, clear label visibility, and the flexibility to support other modalities in a single, cohesive platform.”

Read case study

Encord releases new  Physical AI suite