Encord

Reduces manual annotation effort by leveraging pre-trained vision models (Segment Anything Model 2, custom embeddings) to generate initial predictions that annotators refine rather than label from scratch. Integrates model predictions via API import and supports consensus workflows across multiple annotators to validate AI-assisted suggestions, with per-tier constraints on active learning data volumes (50k for Starter, 1m for Team, 10m for Enterprise).

Provides frame-by-frame and temporal annotation workflows optimized for video data, with advanced object tracking that propagates labels across frames to reduce per-frame labeling effort. Supports multi-modal sensor fusion (RGB-D, LiDAR + video) for autonomous driving and robotics use cases, with frame interpolation and keyframe-based workflows to minimize manual frame annotation.

Version control system for annotated datasets with full lineage tracking from raw data through annotation to model training. Supports branching and merging of datasets, rollback to previous versions, and audit trails for all changes (annotations, corrections, metadata updates). Integrates with CI/CD pipelines to enable reproducible model training and enables comparison of model performance across dataset versions.

Extensible framework for defining custom metadata fields, quality metrics, and evaluation criteria specific to domain or use case. Supports custom metadata at item-level (e.g., image source, collection date, environmental conditions) and annotation-level (e.g., annotator confidence, review status). Enables custom quality metrics beyond standard accuracy/consistency measures, allowing teams to define domain-specific quality thresholds and automated quality gates.

AI-powered data agents that autonomously curate datasets by analyzing data characteristics, identifying gaps, and recommending samples for annotation. Agents use embedding-based similarity, statistical analysis, and custom acquisition functions to prioritize high-value samples and suggest data collection strategies. Supports iterative refinement where agents learn from annotation results to improve future recommendations.

Encord offers VPC (Virtual Private Cloud) and on-premises deployment options for teams with strict data governance or compliance requirements. Data remains within the customer's infrastructure, and Encord provides managed services (annotation, quality assurance) with secure data access. This enables teams to use Encord's platform while maintaining control over data location and access.

Encord supports annotation of text, documents, and LLM outputs for evaluation and fine-tuning. Teams can annotate text classifications, named entity recognition, question-answering pairs, and LLM response quality. The platform integrates with LLM evaluation frameworks and supports consensus-based validation of LLM outputs. LLM evaluation is available as an add-on feature.

Specialized annotation workflows for medical imaging (DICOM, NIfTI formats) with domain-specific tools for 3D volume segmentation, multi-slice review, and radiologist-friendly interfaces. Supports ECG time-series and other medical sensor data, with compliance-ready infrastructure for healthcare deployments (on-premises and VPC options available as add-ons).

Automated quality assurance system that detects label errors, outliers, and inconsistencies across annotation jobs using statistical analysis and model-based anomaly detection. Provides label exploration dashboards for root-cause analysis and supports consensus-based error flagging where multiple annotators identify problematic labels. Integrates with annotation workflows to trigger re-labeling or expert review for flagged items.

Intelligent sample selection system using embedding-based similarity and custom acquisition functions to identify high-value samples for annotation. Prioritizes uncertain, novel, or outlier samples to maximize model improvement per annotation dollar spent. Supports custom acquisition functions (Enterprise tier) for domain-specific sample selection strategies, with built-in support for uncertainty sampling, diversity sampling, and query-by-committee approaches.

API and SDK-based automation for triggering labeling jobs, importing predictions, versioning datasets, and integrating annotation workflows into CI/CD pipelines. Supports programmatic job creation with custom metadata, conditional job triggering based on data characteristics, and automated result export for downstream model training. Enables end-to-end data pipeline orchestration without manual UI interaction.

Structured evaluation system for comparing model outputs using RLHF (Reinforcement Learning from Human Feedback), rubric-based scoring, and pairwise comparison workflows. Supports custom evaluation metrics and integrates with annotation workflows to collect human judgments on model quality. Provides model comparison dashboards to identify performance differences across model versions, datasets, or configurations.

Specialized annotation workflows for geospatial and satellite imagery with support for large-scale orthomosaics, multi-spectral imagery, and geospatial metadata (coordinates, CRS, resolution). Integrates with GIS tools and supports annotation of land use classification, object detection in aerial imagery, and change detection across temporal image sequences. Handles high-resolution imagery (gigapixel-scale) with viewport-based annotation to manage performance.

Annotation workflows for unstructured documents (PDFs, scanned images, HTML) with support for text extraction, table annotation, and structured field extraction. Integrates OCR for scanned documents and supports hierarchical annotation (document-level, section-level, field-level) for training document understanding and information extraction models. Enables annotation of complex layouts with multi-column text, tables, and embedded images.

Workforce management system for organizing annotation teams, assigning tasks based on skill level and specialization, and tracking individual annotator performance metrics (accuracy, speed, consistency). Supports in-house annotators, crowdsourced workers, and domain specialist vendors with role-based access control and quality-based task routing. Provides performance dashboards with annotator-level metrics and recommendations for training or reassignment.