Start with the language and context
Tell us the target language, regional context and data type. For speech or text tasks, include any dialect, terminology or annotation requirements.
ABOUT sixuandata
About sixuandata
Connecting the real world.With what comes next in AI.
We bring collection, preparation, annotation and quality delivery together around a shared brief for your AI project.
From the real world to training data
ONE SHARED BRIEF
Shared taskKeep goals, rules and
delivery connected
delivery connected
01Goals & samples
Define scope and priorities
02Production & review
Apply rules, record differences
03Versions & delivery
Link files to review evidence
01Context
Understand where data is used
02Guidelines
Align tasks and quality criteria
03Delivery
Make results usable and reviewable
WHO WE ARE
Data prepared for the way your team will use it.
sixuandata is the data services brand of Nanchang Sixuan Technology Co., Ltd., working with AI development and data teams.
A pilot establishes the guidelines. Review and correction records document decisions. Each delivery includes a file index and version notes.
GLOBAL CONNECTIONS · LOCAL UNDERSTANDING
Across borders. Connected by data.
We work with partners across Asia, Europe and North America, with language support for international data projects.
Partner locations
07PARTNER COUNTRIES ACROSS THREE REGIONS
Asia
- Pakistan
- Afghanistan
- Singapore
Europe
- Italy
- France
- United Kingdom
North America
- United States
Supported languages
06- English
- French
- Italian
- Urdu
- Pashto
- Arabic
Discuss the language, task and data requirements for your project.
Define the project before scaling
Align data sources, access arrangements, review criteria and deliverables at the start. Use a pilot to clarify the rules before expanding the work.
HOW WE THINK
Principles that shape the work.
Clear agreements, reviewable results and timely feedback form the basis of this working approach.
- 01
Agree on the scope first
Start with the use case, define objects, coverage and acceptance criteria, then use pilot samples to resolve differences in interpretation.
Practical outputRequirements and sample confirmation - 02
Make quality checks traceable
Translate quality requirements into checks, and keep issue and revision records so decisions can be reviewed later.
Practical outputReview records and issue lists - 03
Bring feedback into the next batch
Turn usage feedback into specific rules, distinguish current corrections from future guideline changes, and keep versions consistent.
Practical outputChange records and version notes
WORKING TOGETHER
A shared project brief connects every role.
Project coordination, collection, annotation, quality review and delivery work from shared guidelines, with responsibilities and communication agreed for each project.
SHARED REFERENCE
Project goals · Data guidelines · Acceptance criteria
Keep every role aligned on the same version, from kickoff to delivery.
Project coordination
Align scope, milestones and communication; organize requirement changes and open questions.
Project plan / decision logCollection & annotation
Carry out data tasks against the guidelines and flag edge cases or samples needing clarification.
Task outputs / issue feedbackQuality review
Review samples and batches against agreed criteria, then track corrections and recheck results.
Review records / recheck resultsData delivery
Check files, formats and manifests, and prepare version notes and delivery scope.
Data files / delivery notesLET’S BUILD WITH DATA
Start with a concrete data need.
Share your use case, data type or current challenge, and outline the questions to resolve next.