Multimodal annotation
Annotate images, videos, audio, text, DICOM, HTML, geospatial data, LiDAR, ECG, and other multimodal inputs in one platform.
Encord
ClaimEncord is a multimodal data platform for AI teams to manage, annotate, curate, align, and evaluate training data across images, video, audio, text, and sensor workflows.
What Encord is
Encord is a multimodal data layer for AI teams that need to manage, curate, annotate, align, and evaluate large datasets across the model lifecycle. The product is positioned for physical AI and enterprise use cases, with support for data from sensors, video, text, and related modalities.
The platform combines annotation, curation, model alignment, and evaluation in one system. Source pages describe native multimodal workflows, human-in-the-loop review, and API/SDK-first deployment, with options that include cloud, VPC, and on-prem setups.
Core capabilities
Workflow orchestration
Use customizable workflows, role-based access controls, task assignment, and multi-stage reviews to manage labeling and review at scale.
AI-assisted labeling
Apply AI-assisted labeling tools such as model prediction import, SAM 2 support, object tracking, interpolation, and advanced object tracking.
Data curation and management
Search, curate, and manage datasets with multimodal search, outlier detection, image duplication detection, embeddings, and dashboards.
Evaluation and feedback loops
Run label validation, label exploration, error detection, model evaluation, model comparison, and active learning pipelines.
Enterprise deployment options
Use cloud, VPC, or on-prem deployments, plus API/SDK-first access and zero data migration, to fit existing infrastructure.
Where Encord fits
Physical AI training data
Build and label training datasets for robotics, autonomous vehicles, drones, and other physical AI systems that rely on synchronized sensor streams and 3D data.
Multimodal annotation operations
Set up human-in-the-loop workflows for annotating and reviewing images, videos, audio, text, and medical data with quality controls and performance tracking.
Data curation and edge-case discovery
Find rare edge cases, close distribution gaps, and prepare production data using embedding-based search, model-in-the-loop curation, and dataset management tools.
Model evaluation and alignment
Evaluate production models with rubric-based review, pairwise comparison, RLHF, and label/model analytics to identify failure modes and feed them back into training.
Enterprise team rollout
Organize annotation and review across distributed teams with multiple workspaces, SSO, role-based access, and enterprise support.
Pros and Cons
Pros
- Covers multiple data types and workflows in one platform, including annotation, curation, evaluation, and model alignment.
- Supports multimodal and video-native annotation, including LiDAR, audio, text, DICOM, geospatial data, and sensor fusion.
- Includes workflow controls such as role-based access, task assignment, review stages, and performance analytics.
- Offers deployment flexibility with cloud, VPC, and on-prem options, plus API/SDK-first access.
- Targets large-scale teams with enterprise features such as multiple workspaces, SSO, and enterprise SLA and support.
Cons
- The public source does not provide a full integration catalog or detailed implementation requirements.
- Pricing and plan limits are only partially disclosed in the source, so buyers may need a sales conversation for complete scoping.
FAQ
What kinds of data can Encord label?
Encord is designed for multimodal data labeling across images, videos, audio, text, DICOM, HTML, geospatial data, and related sensor inputs. The platform centers on customizable workflows, AI-assisted labeling, and human-in-the-loop review.
How is Encord deployed?
The source describes Encord as API/SDK-first and says there is zero data migration, with data remaining in your cloud. It also presents cloud, VPC, and on-prem deployment options on the pricing page.
What pricing plans does Encord offer?
Pricing is organized into Starter, Team, and Enterprise plans. Starter is for individuals and small teams, Team adds data agents and analytics, and Enterprise adds multiple workspaces, SSO, enterprise SLA and support, and VPC/on-prem deployments.
Can teams customize labeling workflows?
Yes. The source says Encord supports customizable workflows with role-based access, task assignments, review stages, and workflow automation.
Does Encord support AI-assisted labeling models?
The source supports AI-assisted workflows and integration with models such as GPT-4o, LLaMa 3.2, and Gemini 1.5 Flash on the annotation page, but it does not provide a full public integration list.
Quick Facts
- Category
- Multimodal data platform
- Primary users
- AI teams, enterprise teams, and physical AI teams
- Core workflow
- Manage, curate, annotate, align, and evaluate training data
- Supported data types
- Images, video, audio, text, DICOM, HTML, geospatial data, LiDAR, ECG, and sensor data
- Pricing
- Starter, Team, and Enterprise plans
- Deployment
- Cloud, VPC, and on-prem options