Turn Raw Data Into Competitive AI Advantage

YPAI supports image annotation (bounding boxes, polygons, semantic segmentation, keypoints), video annotation (object tracking, event labelling), NLP annotation (named-entity recognition, intent, sentiment), audio and speech annotation (transcription, diarisation, prosody), and 3D / LiDAR point-cloud annotation for autonomous-vehicle perception stacks. All modalities run inside a single quality and compliance regime so multimodal projects share the same review, provenance, and audit-trail pipeline. See AI data labeling for the labelling-versus-annotation distinction.

YPAI runs a multi-stage review pipeline: spec calibration, double-pass annotation on dispute-prone slices, expert adjudication, and a final QA sweep against task-specific acceptance criteria. Each batch ships with an inter-annotator-agreement (IAA) report and a per-label confusion matrix so machine-learning teams can target re-work where it materially affects training. Sample sizes are statistically scoped to the project rather than fixed.

Yes. Annotation pipelines are GDPR-native: lawful basis, purpose limitation, data minimisation, and Article 35 DPIA scaffolding are part of the engagement, not a checklist that arrives at the end. Personal data is processed inside EU/EEA infrastructure under a signed Data Processing Agreement (DPA), and subject-rights requests (access, rectification, erasure) route through [email protected]. See data ethical framework for the underlying governance.

YPAI has delivered annotation across 150+ languages and dialects, with native-speaker reviewers concentrated in European, Nordic, and major Asian markets. Lower-resource languages are quoted on a per-project basis because the limiting factor is reviewer recruitment, not pipeline capacity. Multilingual projects route through a single delivery lead, so glossary, style guide, and IAA targets stay consistent across languages.

YPAI is an Oslo-headquartered EU/EEA-native operator: data lives under EU jurisdiction by corporate structure, not by contract terms. The US CLOUD Act does not reach YPAI infrastructure. Engagements are run by in-house teams with sector specialists (automotive OEM, healthcare ASR, financial documents), not a public crowd marketplace. Pricing is per-project after a feasibility scope, not per-task with hidden minimums.

Yes. YPAI handles DICOM, NIfTI, and FHIR-bundled imaging with clinician reviewers contracted for the modality. Data is processed inside EU residency by default and the pipeline aligns with GDPR Article 9 special-category rules. Specific certification regimes (HIPAA-aligned workflow, ISO 13485, IEC 62304) are scoped per project; YPAI does not assert blanket certifications and documents the exact controls in the statement of work.

YPAI prioritises engagements where the annotation work is non-trivial and the compliance posture matters. Below roughly a single-batch pilot (a few thousand items for image / NLP, a small audio corpus for speech) the engagement model rarely justifies the scoping cost on either side. Pilots are common and welcomed; the scoping call confirms whether the brief is a fit before any quote.

YPAI replies inside one EU business day after a submission to /contact-us/ with a feasibility read, the next concrete step, and an estimated scope window. The first reply is from an engineer or delivery lead with context on the brief, not a generic confirmation email.