Multimodal Data Production and Governance Platform
Data Annotation Platform
High-quality data powers high-quality AI.Covers data ingestion, task distribution, multimodal annotation, quality inspection, version management, and data asset development.
Turn fragmented source data into high-quality, traceable, and reusable data assets
The Data Annotation Platform covers ingestion, task design, intelligent pre-annotation, human collaboration, multi-level quality control, versioning, and asset development. Project owners can track the origin, status, and quality of every batch while production teams work consistently from shared standards.
Image, video, text, speech, and point-cloud work is organized in one project space through shared label systems, role permissions, task batches, and operation records. Intelligent pre-annotation works alongside human review, while rule validation and sampling embed quality control throughout the production path.
From source-data intake, task allocation, and workforce coordination to acceptance, version archiving, and delivery, each stage retains a visible status and lineage. Teams can complete an immediate training-data request while also building reusable datasets, annotation standards, and quality practices for subsequent model iterations.
Supply dependable AI data through a standardized processSupply dependable AI data through a standardized process
Unified Multimodal Production
Organize image, video, text, speech, and point-cloud tasks in one platform with less tool fragmentation.
Unified data productionTraceable Quality Control
Embed rule validation, human review, and sampling records throughout every production stage.
Traceable qualityReusable Data Assets
Preserve versions, label systems, and production lineage for consistent training, evaluation, and iteration.
Reusable versions
Platform capabilities across the complete data-production lifecycle
Multimodal Annotation Tools
Support classification, detection, segmentation, keypoints, text sequences, transcription, and point-cloud tasks.
Standardized Task Workflows
Configure roles, batches, progress, and delivery standards to keep large teams synchronized.
Pre-Annotation and Review
Combine model-assisted pre-annotation with human correction to reduce repetitive work and improve samples.
Data Governance and Security
Protect sensitive data and production activity through permissions, masking, audit, versioning, and lineage.
Give every data batch a clear production and quality trail
- Input · Source data
Ingest and Clean
Receive source data and complete format validation, deduplication, and secure preprocessing.
- Process · Standards
Configure Standards and Tasks
Define label systems, examples, roles, quality rules, and production batches.
- Collaborate · Label and inspect
Annotate and Inspect
Combine pre-annotation, human production, review, and sampling to improve consistency.
- Output · Versioned assets
Deliver and Version
Release training or evaluation data by version with retained lineage and quality reports.
Meet the data needs of different models and industries
Computer Vision Training
Produce detection, segmentation, tracking, and keypoint data for visual recognition and analysis.
Language and Speech Models
Create classification, entity, dialogue, transcription, and preference-quality datasets.
Autonomous Systems and Robotics
Process video, point-cloud, and multi-sensor data for environmental understanding and behavior learning.
Private Enterprise Data Governance
Organize industry corpora inside secure boundaries for use by enterprise models.
Balance production scale, quality, and security
- Unified Multimodal ProductionCovers image, video, text, speech, and point-cloud task forms.
- Batch and Role CollaborationOrganizes scaled production through batches, roles, and review gates.
- Pre-Labeling with Human ReviewPuts pre-labeling, human review, and sampling in one quality loop.
- Traceable Data Lineage and QualityGoverns data within permission, audit, masking, and lineage boundaries.
- End-to-End Security and ComplianceKeeps production inside explicit security and compliance boundaries.
Bring product capabilities into real business
Supply dependable AI data through a standardized processWork with Qukai to define the scenario, technical path, and delivery plan.