Training data managed by people who understand what models need.
Most annotation vendors are BPOs with no ML context. Trodas is an engineering team that has led 50-person annotation operations for Fortune 500 vision programs and built the Python QA automation that kept quality above SLA. The studio sets up tooling, manages the workforce, and automates quality control — so your models train on data you can trust.
annotators led on enterprise programs
annotation and QA leadership on production ML projects
quality guarantees enforced by automated QA scripts
Deliverables, not deliverable-shaped promises.
- Image, video, and text annotation (detection, segmentation, classification)
- OCR and document annotation programs
- Label Studio and CVAT pipeline setup and configuration
- Python-based QA automation and inter-annotator agreement tracking
- Annotation guideline authoring and team training
- Managed teams scaled to your volume and deadline
Stack we typically use
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How is annotation work priced?
Per-item or per-hour depending on task complexity, with a free pilot batch so you can verify quality before committing volume. Transparent unit economics — no hidden minimums.
How is quality controlled?
Layered QA: automated Python validation catches structural errors, statistical sampling catches drift, and senior reviewers audit edge cases. Quality reports are delivered with every batch.
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