Requirement Review
We review the data type, target language or market, labeling rules, platform constraints, volume, delivery format, and security requirements before production planning.
Quality Control, Secure Operations, Compliance Awareness, and Traceable Delivery
We use a structured production process to align requirements early through trial annotation, manage quality during production, and make final deliverables traceable for review and acceptance.
Send Project RequirementsQuality Built into Every Step
Trial Annotation and Requirement Alignment
We prepare task instructions, annotation guidelines, and sample outputs, then run trial annotation to align the requirements between both teams and to ensure all project members apply the same rules before full-scale production.
Production with Machine and Human QA
Production may combine automated pre-checking, manual review, proportional sampling, and cross-audit to reduce quality drift during large-scale data work.
Rework and Acceptance Checks
Nonconforming data goes through a closed loop of rejection, correction, and re-inspection, helping issues surface early and keeping final outputs aligned with agreed standards.
Traceable Delivery and Iteration
Deliverables may include processed data files, statistics reports, QA records, rework logs, and acceptance documentation, supporting later review and model iteration.
QA Controls
Machine pre-check
Automated checks flag format issues, missing fields, audio anomalies, and other rule-based errors before manual review begins.
Manual review
Reviewers check content, labels, transcription quality, boundaries, and category use against project specifications.
Batch sampling
Sampling by batch, language, task type, or delivery stage helps detect quality drift and batch-level issues.
Cross-review
Independent reviewers sample completed work to check consistency, catch missed issues, and validate review quality.
Rework loop
Problematic data is returned for correction, rechecked, and logged so recurring issues can be addressed quickly.
Compliance Requirement Identification: Identify applicable laws and regulations, confidentiality requirements, data usage boundaries, and platform operation rules before project launch.
Controlled Environment Operations: Support client-designated platforms, systems, networks, VPN environments, physical or logical isolation, overseas sites, and designated offshore IP environments where needed.
Permission-Controlled Delivery: Assign minimum necessary permissions by role, use masking, encryption, download prevention, and operation logs, and retain QA and delivery records for later audit and traceability.
Secure operations
Secure, Compliance-Aware Project Operations and Delivery
For projects involving sensitive data, cross-border work, localized collection, or client-owned platforms, we can adjust the operating environment, access rules, and delivery workflow according to project requirements, applicable laws, and client security policies.
Security and Delivery FAQ
Can you work inside a client-designated platform?
Yes. We can organize work instructions according to client platform rules, train project members, and carry out task assignment, annotation, review, and delivery as required.
Can data remain within a designated network or controlled environment?
Yes. Projects can be organized within a client-designated network, dedicated system, VPN, overseas site, or designated offshore IP environment as required.
Can you support project compliance and confidentiality requirements?
Yes. Before project launch, confidentiality obligations, data usage boundaries, operating methods, and delivery requirements can be clarified and implemented through personnel training and process management.
Can QA and delivery records be traced?
Yes. Deliverables may include data statistics, pre-check records, review records, sampling results, rework logs, and acceptance notes according to project requirements.
Do you support trial annotation and rule alignment before full production?
Yes. Trial annotation can be used to validate task rules, sample difficulty, quality standards, and delivery formats, helping both sides align understanding before full-scale production.