MetisIntelligent Data Annotation Platform
MergeAI Pre-labeling、Multi-layer Quality AssuranceandIntelligent Workflow
Build an enterprise-grade data labeling platform.300% productivity boost，Accuracy up to 99.9%
Annotation Tool
Supports annotation for all data types: point clouds, video, audio, images, and text.50+Annotation Type
Covers complex scenarios such as autonomous driving, embodied intelligence, and large model training.
Point Cloud Annotation
Five-view linkage (front/back/left/right/top), supporting 3D cuboids, semantic segmentation, and multi-frame tracking. Includes 20+ professional tools such as point cloud zooming, reference lines, render mode switching, and grouping management.
Embodied AI Annotation
VLA (Vision-Language-Action) multimodal data annotation for humanoid robots and robotic arms, supporting precise labeling of manipulation trajectories, grasp poses, and force control data to advance embodied AI breakthroughs.
Video Annotation
Supports 2D/3D bounding box, semantic segmentation, keypoint annotation, and frame-by-frame labeling. Features timeline editing, sub-task annotation, temporal tracking, and behavior analysis. Optimized for smart security, autonomous driving, and other scenarios.
Voice Annotation
Supports speech-to-text transcription, audio segmentation, speaker verification, and sentiment analysis in major global languages and dialects. Designed for smart customer service and voice assistant applications.
Image Labeling
Supports 2D bounding boxes, polygon segmentation, image classification, and keypoint annotation. Delivers 30+ efficient tools including multi-select, copy, rotate, auto-interpolation, and shared-edge cutting, processing over 10 million images daily.
Text Labeling
Provides multi-level NLP annotation including entity recognition, relation extraction, sentiment analysis, text classification, and syntactic parsing. Supports custom tag schemas tailored for large model training.
Core Features
AI pre-annotation, multi-level quality assurance, intelligent workflow, analytics reports, role-based access control, data security
Six Core Capabilities Powering an Enterprise-Grade Annotation Platform
Smart Labeling
AI-powered pre-annotation, assisted labeling, and active learning drive a three-pronged approach that automatically recommends labels, boosting labeling efficiency by over 300%.
Multi-layer Quality Assurance
Multi-stage quality assurance system featuring automated, algorithmic, and manual reviews. Supports random sampling and data rework to ensure annotation accuracy of 99.9%.
Statistical Report
Multi-dimensional data reports covering workload statistics, efficiency analysis, quality dashboards, and operator performance, with support for custom export and visualization.
Role Permissions
Three-tier role system: Admin, Project Manager, and Operator with fine-grained permission control, custom roles, and data isolation.
Workflow Engine
Configurable annotation, quality assurance, and delivery workflows with support for serial, parallel, and conditional branching to accommodate complex business scenarios.
Data Security
Multi-layer encryption, dynamic watermarks, activity logs, and permission audits. Fully compliant with security certifications to ensure zero data leakage.
Platform Technical Architecture
Adopt a layered software architecture to ensure system stability, security, and scalability.
Storage Layer
MySQL distributed database + S3 object storage + Redis caching + RocketMQ message queue, supporting PB-scale data storage
Compute Layer
Serverless Computing Platform + AI Model Inference + BI Analytics System for Powerful Data Processing
Service Layer
Microservices architecture with three dimensions—accounts, workflows, and data—for multi-dimensional, fine-grained management.
Application Layer
React-based frontend framework offering data annotation, project management, quality inspection, and statistical reporting scenarios.
Multi-layer quality assurance process
System, algorithmic, and manual multi-stage quality inspections
Ensure annotation accuracy reaches99.9%
Multi-round Quality Assurance
When creating a labeling task, you can define multiple review or quality assurance nodes within the workflow, supporting a multi-stage flow of labeling → first review → quality check.
Random Sampling
After configuring workflow nodes, you can select random sampling by ratio or apply filters based on tags, personnel, time ranges, and more to improve sampling accuracy.
Data Correction
Annotation questions follow the workflow node data flow. If issues arise, support full return, partial return, or single-item return to any workflow node.
Statistical Reporting System
Multi-dimensional data reports on workload, efficiency, and quality
Support person, daily, and task-based statistics for data-driven decision-making.
Workload Report
Track operator workload by person, day, or task, including metrics such as submissions and rework.
Efficiency Report
Track annotation efficiency by person, day, or task, including metrics like average time spent and completion count.
Quality Report
Track annotation accuracy by person, day, or task, including question pass rate and result accuracy.
Operator Report
Daily statistics on active annotators and reviewers to support personnel performance management
Annotation Results Statistics
Aggregate annotation results by project and task; view data labeling progress and result distribution
Custom Error Tag
Support custom error tags for annotations, with annotation count and status tracking, plus accuracy calculation.
Six Quality Service Commitments
We provide data assurance for your AI projects with professional, efficient, and secure services.
Reliability
Always ready to serve with guaranteed speed, supporting up to 100M+API requests per day.
reactivity
Respond to customers promptly, take proactive service initiatives, and receive dedicated project manager support throughout.
value for money
Deliver high-quality data services at the best value, reducing costs by over 70%.
Accuracy
Ensure high-quality data delivery to customers with annotation accuracy of 99.9%.
Efficiency
High-efficiency service with faster delivery; AI assistance boosts annotation efficiency by 50%–80%.
Security
Data Security Assurance: Multi-layer Encryption, Access Control, and Dynamic Watermarking to Prevent Leaks
Operation Flow
Standardized six-step process to ensure efficient, high-quality project delivery
Create Project
Create labeling project, configure labeling type, label schema, quality inspection rules, and user roles with permissions
Import Data
Batch import data for labeling. Supports images, videos, point clouds, text, and audio. Automatically syncs with external data sources.
Smart Labeling
AI pre-labeling generates initial results, human annotators refine and perfect them, intelligent task distribution ensures efficiency, and real-time assistance boosts annotation speed.
Multi-round Quality Assurance
Automated system QC, algorithmic consistency checks, and manual spot reviews ensure accuracy of 99.9% through multi-stage validation.
Data Correction
Automatically flag quality issues, with support for bulk repair, targeted repair, and priority sorting to ensure 100% of issue data is corrected.
Acceptance Delivery
Visualize data validation with flexible delivery options: API integration, file export, and structured database ingestion.
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