Encord
Data infrastructure platform for training physical AI on multimodal sensor data.
Pricing
About Encord
Encord is a data infrastructure platform designed for AI teams building physical AI systems and enterprise AI applications. The platform enables teams to manage, curate, annotate, and align large-scale multimodal datasets from various sources including video, images, LiDAR, audio, text, and sensor streams. Encord handles the full data pipeline from pre-training through post-deployment feedback loops, supporting tasks like annotation, data collection, RLHF orchestration, and model evaluation. The platform is particularly focused on physical AI—robotics, autonomous vehicles, drones, and industrial automation—but also serves enterprise teams across healthcare, defense, and generative AI. It offers both a self-service platform with native video and sensor annotation capabilities, plus managed data services with domain experts. A key distinction is its multimodal-by-design architecture that unifies different data types in single workflows, and its emphasis on staying zero-migration compatible with customer cloud infrastructure.
At a glance
- Company
- Cord Technologies, Inc. (est. 2021)
- Platforms
- Web, API, SDK
- API
- Available
- Last verified
- June 2026
Who It's For
- •Physical AI teams building robotics, autonomous vehicles, and drones
- •Enterprise AI teams across healthcare, defense, and industrial sectors
- •Computer vision teams managing large-scale multimodal datasets
- •Generative AI and LLM teams focused on model alignment and RLHF
- •Organizations requiring production-grade data infrastructure and annotation services
How It Works
- 1Ingests multimodal data (video, images, audio, LiDAR, text, documents, geospatial) from various sources including sensors, feeds, or collection facilities
- 2Provides customizable workflows for annotation, labeling, and quality control with built-in label lineage tracking for production scale
- 3Uses embedding-based search and model-in-the-loop curation to identify edge cases and distribution gaps before deployment
- 4Orchestrates post-training workflows including RLHF, rubric-based evaluation, and pairwise comparisons for models in production
- 5Captures deployment feedback and routes model failures back into training pipelines
How to Use Encord
- 1Connect data sources through API/SDK or upload multimodal datasets
- 2Design annotation and labeling workflows using the customizable platform interface
- 3Use embedding-based search to curate and filter data for specific use cases
- 4Configure RLHF and evaluation workflows for model alignment and post-training
- 5Access managed annotation and data collection services with vetted domain experts
- 6Monitor label lineage and quality metrics throughout the data pipeline
Key Features
- •Multimodal annotation supporting video, image, audio, LiDAR, text, documents, geospatial, and HTML
- •Native sensor fusion and video annotation with built-in quality controls
- •Embedding-based search and model-in-the-loop data curation
- •RLHF orchestration, rubric-based evaluation, and pairwise comparison workflows
- •Managed annotation services with vetted domain experts
- •Physical AI data collection from field operators and teleoperation facilities
- •Label lineage and production-scale quality controls
- •API/SDK-first architecture with zero data migration requirement
- •Cloud-agnostic deployment (data remains in customer's cloud)
Use Cases
- •Training perception models for autonomous vehicles and ADAS systems with multimodal sensor fusion
- •Annotating robotic manipulation and embodied AI data across RGB, depth, LiDAR, and force/torque inputs
- •Managing large-scale video annotation for surgical AI and healthcare applications
- •Curating and evaluating frontier generative AI models with RLHF and alignment techniques
- •Collecting and labeling training data for industrial automation and manufacturing systems
Pros & Cons
Advantages
- •True multimodal-by-design platform unifying video, LiDAR, audio, text, and sensor data in single workflows—rare among competitors
- •End-to-end physical AI focus with managed collection services and teleoperation facilities, not just annotation
- •API/SDK-first architecture with zero data migration keeps customer data in their own cloud infrastructure
- •Trusted by 300+ AI teams including enterprise names like Woven by Toyota, UiPath, and AXA with documented results (e.g., 10x dataset growth, 4x error reduction)
Disadvantages
- •Platform complexity and breadth across multiple modalities and use cases may require significant learning and configuration compared to focused competitors
- •Managed data services require domain expertise matching, which may have capacity constraints during scaling
- •Pricing not transparent on website; customers must request quotes, limiting accessibility for smaller teams or startups
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Frequently Asked Questions
What is Encord?
Encord is a data infrastructure platform designed for AI teams building physical AI systems and enterprise AI applications. The platform enables teams to manage, curate, annotate, and align large-scale multimodal datasets from various sources including video, images, LiDAR, audio, text, and sensor streams.
How much does Encord cost?
Encord is free to use.
Is Encord free?
Yes, Encord offers a free plan you can start with.
What are the best Encord alternatives?
Popular Encord alternatives include Datature, Gentrace, Labelbox.
What is Encord used for?
Encord is commonly used for Training perception models for autonomous vehicles and ADAS systems with multimodal sensor fusion, Annotating robotic manipulation and embodied AI data across RGB, depth, LiDAR, and force/torque inputs, Managing large-scale video annotation for surgical AI and healthcare applications.
Does Encord have an API?
Yes, Encord offers an API for developers.
What platforms does Encord support?
Encord is available on Web, API, SDK.
Information Accuracy
Please note: While we regularly update all tool information including descriptions, features, pricing, and other details, this information may change over time as tools evolve and update their offerings. For the most current and accurate information, we recommend visiting the official website directly. Our goal is to provide you with comprehensive and up-to-date information to help you make informed decisions.