Production-Grade
Data Annotation
Your ML model is only as good as its training data. We provide human-labeled datasets with rigorous quality control for NLP, computer vision, audio, and video tasks. No crowdsourcing lottery — trained annotators following your guidelines.
From startups training their first classifier to research labs preparing benchmark datasets, spacedrift.in delivers annotation that is accurate, consistent, and fast. We scale from hundreds to millions of labels without compromising quality.
Capabilities
Every modality. One team.
We handle text, image, document, audio, and video annotation with specialized pipelines built for each data type. Complex multi-modal? We do that too.
Text Annotation
Named entity recognition, sentiment analysis, intent classification, text categorization, relation extraction, and coreference resolution. Supports 12+ languages with native annotators.
Image Annotation
Bounding boxes, polygon segmentation, keypoint detection, semantic labeling, instance segmentation, and panoptic annotation. Pixel-level precision for autonomous driving, medical imaging, and retail.
Document Annotation
Table extraction, form field mapping, OCR correction, and structured data extraction from invoices, receipts, and contracts.
Audio Annotation
Speech transcription, speaker diarization, emotion detection, audio event classification, and music tagging.
Video Annotation
Object tracking, action recognition, temporal segmentation, frame-by-frame labeling, and activity detection.
98%+
Average annotation accuracy across all projects
3x QC
Triple quality check on every annotation batch
48hr
Turnaround for pilot batches and sample reviews
8+
Output formats supported natively
Output
Your format. Our delivery.
We deliver in whatever schema your pipeline expects. Standard formats ship by default; custom schemas are configured in the pilot phase.
JSON / JSONL
Universal
COCO
Computer Vision
CSV / TSV
Tabular
spaCy / CoNLL
NLP
YOLO
Object Detection
Pascal VOC
XML Format
Parquet
Big Data
Custom
Your Schema
Pipeline
How annotation works.
Every project follows a structured pipeline with built-in quality gates. You see progress and quality metrics at every stage.
Requirements & Sample
Send us your data samples, annotation guidelines, and target format. We review feasibility and create a pilot plan within 24 hours.
Pilot Batch
We annotate a small batch (50-100 samples) for your review. This calibrates our understanding of your guidelines and sets quality benchmarks.
Production Run
After pilot approval, we scale to full production with trained annotators. Every batch passes triple quality control before delivery.
Delivery & Iteration
Annotated data delivered in your format with quality reports. Feedback from your model training informs subsequent batches for continuous improvement.
Need labeled data
for your model?
Send us a sample dataset and your annotation guidelines. We respond with a pilot plan and quote within 24 hours.
contact@spacedrift.in