Encord vs Invisible Technologies

Data Agents automate Encord data pipelines by integrating humans, state-of-the-art models and a customer's own models into data workflows. They handle tasks such as pre-labeling, object segmentation and tracking, video captioning, audio transcription and sentiment analysis, combined with human-in-the-loop quality assurance.

The multimodal data layer for physical AI: one platform for managing, curating, annotating and aligning sensor, video, image and text data at petabyte scale. The modules a buyer licenses — Annotate, Index and Active — are recorded separately.

Encord Active is Encord's model and data evaluation product. It evaluates and validates models against their data to surface, curate and prioritise the most valuable data for training and fine-tuning, covering model robustness checks, drift and failure-mode detection, automated label-error detection, and active learning workflows across images, video, 3D/LiDAR, audio and documents.

Encord Annotate is Encord's multimodal data labeling product, used to annotate and review images, video, audio, text, documents, DICOM, LiDAR and geospatial data. It provides AI-assisted labeling, customizable ontologies, human-in-the-loop review workflows and quality-control tooling for managing large annotation teams.

Managed annotation service: Encord supplies vetted domain experts for a customer's task and runs the projects, with an evaluation workflow built around the customer's own spec rather than volume alone.

Managed collection of real-world training data for physical AI: in-field operators, teleoperation facilities and configurable lab environments gathering the embodied, egocentric and sensor data a robotics model needs.

Encord Index is Encord's multimodal data curation and management product. It lets teams search datasets with natural language and similarity search across video, image, audio, LiDAR, text, document, geospatial and HTML files, filter by 40+ data metrics and custom metadata, visualise outliers on embeddings plots, and remove duplicates and poor-quality data via Collections. Data stays in the customer's own cloud with 'zero data migration required'.

End-to-end data service for robotics, autonomous systems and embodied AI: data collection (in-field operators, teleoperation), curation, LiDAR/point-cloud/multi-camera annotation, VLA/VLM action-captioning, and post-deployment feedback loops, with on-prem/VPC deployment.

Documents and automates manual business workflows: maps how work actually gets done, then runs every step automatically, routing to the right AI system or person and enforcing quality checks.

Deploys agents that carry out multi-step work with tool use and an audit trail.

Evaluates AI systems for quality, safety and accuracy against criteria a customer defines.

Recruits and manages experts who produce training data, evaluations and reinforcement-learning environments for AI labs.

Network of 24,000+ vetted domain experts, continuously screened and organized by skill, language and domain expertise, for AI data labeling, testing and edge-case handling.

Data platform that pulls messy, scattered data from across a company's systems into one governed place, automatically cleaning and organizing it into an AI-ready foundation.