Codoop designs annotation workflows and training data pipelines so your models learn from clean, auditable labels, not noisy spreadsheets.
High-performing models fail more often on bad labels than on bad architecture. We build annotation systems that combine human review, automated pre-labeling, and clear taxonomies so every sample is traceable from source to training set.
Our pipelines support vision, text, and structured events. Reviewers work in purpose-built UIs with consensus rules, inter-annotator metrics, and escalation paths for ambiguous cases. Active learning loops surface the samples that move model accuracy the most.
Exports land in the formats your training stack expects, COCO, YOLO, JSONL, Parquet, with versioned snapshots you can roll back. When you own the pipeline, you own the competitive moat: data that competitors cannot buy off a shelf.
We integrate with your storage and MLOps tools so annotation is a first-class stage of the product, not a one-off freelance project.
Frequently Asked Questions
Do you provide annotators or only the software?
We build the annotation platform and QA process. You can staff reviewers in-house, use your preferred vendor, or ask us to help stand up a hybrid team with clear SLAs and audit trails. Codoop delivers this as production software you own, in 14-day sprints, with staging demos and a full source handover.
Which data types can you label?
Images, video frames, documents, chat transcripts, sensor events, and structured records. We tailor schemas to your domain rather than forcing a generic template. Codoop delivers this as production software you own, in 14-day sprints, with staging demos and a full source handover.
How do you prevent label drift over time?
Versioned guidelines, golden-set audits, and periodic recalibration reviews keep definitions stable as your product and edge cases evolve. Codoop delivers this as production software you own, in 14-day sprints, with staging demos and a full source handover. Work starts from a written architecture note and finishes with repositories, runbooks, and full client ownership of the code.