Piezee delivers precision data annotation at scale — image, video, text and audio labeling with enterprise-grade QA, dedicated project managers, and 48-hour pilot turnaround.
Services
From raw assets to production-ready labeled datasets — at any volume, any modality, any domain.
Bounding boxes, polygons, key points, semantic segmentation. Supports JPEG, PNG, TIFF, RAW with custom label taxonomies.
Frame-by-frame tracking, action recognition, scene segmentation for autonomous vehicles, surveillance, and sports AI.
Named entity recognition, intent classification, sentiment analysis, and RLHF preference ranking in 30+ languages.
Transcription, speaker diarization, emotion detection, and audio event tagging for voice AI and ASR systems.
Pixel-perfect panoptic and instance segmentation for medical imaging, autonomous driving, and satellite imagery.
Bespoke annotation pipelines around your ontology, tooling, and domain. RLHF, multi-modal, any use case engineered.
Why Piezee
When model performance depends on training data quality, you need more than a crowdsourcing tool.
Annotator → peer review → senior QA → PM sign-off. IAA measured throughout. Only batches above your threshold ship.
Ramp from 2 to 200+ annotators in days. Recruiting, training, and management fully handled by Piezee.
One expert PM owns your delivery. No tickets, no bots — direct access, proactive communication, full accountability.
NDAs, AES-256 encryption, role-based access, zero retention. GDPR and HIPAA-compatible workflows on request.
Our Process
A structured workflow that eliminates ambiguity and keeps your ML roadmap on track.
Deep-dive into your task, ontology, edge cases and ML objectives to build a precise guideline.
200–500 sample assets annotated and reviewed jointly to calibrate quality before production begins.
Dedicated team runs production at agreed throughput, following calibrated guidelines precisely.
Multi-layer quality pass per batch. Failed assets reannotated — never delivered below threshold.
Datasets in COCO, YOLO, Pascal VOC, JSON, CSV or custom format via secure encrypted transfer.
Use Cases
Domain-specialized annotators trained in industry-specific object types and edge cases.
LiDAR 3D bounding boxes, lane marking, driveable surface segmentation, and pedestrian key points for perception stack training.
DICOM segmentation, radiology NLP, pathology slide annotation under HIPAA-compatible data handling protocols.
RLHF preference ranking, intent classification, NER and multi-turn conversation labeling for GPT-class model training.
Product attribute tagging, visual similarity labels, shelf detection annotation for recommendation and inventory AI.
Grasping pose estimation, defect detection, object manipulation video annotation for robotic learning systems.
Player tracking, action recognition, pose estimation, event tagging across multi-camera broadcast footage.
Testimonials
"Piezee's annotation quality directly improved our object detection mAP by 6 points. Their QA process is genuinely rigorous — not just claimed. The dedicated PM made coordination seamless across our distributed team."
"We needed 200K LiDAR frames in 8 weeks with very specific class hierarchies. Piezee ramped a 40-person team in 4 days and delivered on time with 98.9% accuracy. Remarkable execution at every stage."
"As a healthcare AI company, data security isn't optional. Piezee's NDA process, encrypted transfers and role-based access gave our legal team everything they needed. Medical annotation quality was exceptional."
Tell us your annotation challenge. A real project manager reviews every inquiry and replies within 24 hours with a custom quote and timeline.
✓ NDA on request ✓ Free pilot project ✓ 24-hour response
FAQ
Get in Touch
No automated responses. A real project manager reviews every inquiry and replies within one business day with a custom quote tailored to your ML goals.
Our team will review your project and reply within 24 hours.