AI Data Operations
Data labelling, annotation, classification and quality checks.
Explore service →Managed AI data operations
Human intelligence for AI data and quality operations.
We help AI teams manage the human work behind data preparation, model evaluation and quality assurance.
Our trained, tested and managed contributors handle tasks such as data annotation, AI output evaluation, preference ranking and visual quality checks. Each engagement starts with a defined task, agreed quality standards and measurable acceptance criteria.
Customers buy accepted outputs, not simply access to a pool of workers.
The human layer
The human layer behind reliable AI
AI teams need people to label data, evaluate model outputs, identify errors and apply human judgment where automated checks are not enough.
We organise this work into structured delivery processes with clear instructions, task-specific training, quality checks and documented results. The objective is straightforward: deliver work that meets the agreed requirements.
What we do
Managed work for human-intensive AI workflows
Each service is scoped around the required output and quality standard.
AI Output Evaluation
Human assessment using defined rubrics, ranking and error analysis.
Explore service →Visual Quality Assurance
Review of images and visual assets against requirements.
Explore service →Quality Review
Independent review of inconsistent or disputed results.
Explore service →How we work
A defined process, from task to accepted output
Agree on the task
Set the objective, outputs, standards and acceptance criteria.
Train and assess
Prepare contributors with task instructions and readiness checks.
Check quality
Use task-appropriate checks, escalation and rework.
Start with a defined pilot
A practical way to assess fit before scaling.
A pilot uses a specific task and representative sample. Both parties agree on acceptance criteria and how results will be measured.
Scope, delivery capacity, timelines and commercial terms are confirmed after discovery.
Discuss Your Workflow →