We annotate industrial data so factories can deploy AI that actually works. Domain experts. AI-assisted workflows. India-cost advantage.
In June 2025, Meta invested $14.3 billion in Scale AI. Within weeks, Google cut ties. OpenAI, Microsoft, and xAI followed. Hundreds of millions in annotation contracts are now up for grabs. The world's largest annotation company just lost its neutrality.
Generalist BPOs cannot distinguish a weld porosity defect from a surface scratch. Industrial AI needs domain experts, not generic labelers.
Building annotation teams takes 6-12 months and costs $300K+ before a single model is trained. Most factories abandon the effort.
49% owned by Meta. Google, OpenAI, Microsoft, and xAI are actively seeking alternatives. The market leader created a vacuum.
India's $492M annotation market by 2030 has no industrial specialist. The gap is wide open for a focused player.
Annotators trained in manufacturing defect taxonomies: weld defects, surface cracks, pharma packaging, textile flaws. Real industrial expertise — not generic labeling.
Open-source models (YOLO, SAM, DINOv2) fine-tuned on industrial data. Pre-label 70-80% of images automatically. 3x faster, 40% cheaper than manual annotation.
Indian annotator: $3-5/hr vs $25-40/hr in the US. Same quality, fraction of the price. Structural cost moat built into the business from day one.
Global Data Labeling Market (2025). Growing to $19.9B by 2030 at 25% CAGR.
Industrial & Manufacturing Annotation. Smart manufacturing, automotive, medical imaging.
10% of India's $492.4M annotation tools market. ~850 manufacturers at avg $58K spend.
Send us your raw industrial images — defect photos, assembly line captures, quality inspection scans. We handle all formats.
Our fine-tuned models (YOLO, SAM, DINOv2) automatically pre-label 70-80% of your images. Humans refine the rest.
Domain-trained annotators verify, correct, and add precise labels using manufacturing defect taxonomies. No guesswork.
Automated consistency checks + senior reviewer sign-off. Every annotation meets your accuracy threshold before delivery.
Receive production-ready labeled datasets. Plug into your ML pipeline. Watch your defect detection accuracy soar.
Transparency is a feature, not a bug. We know exactly what we need to build.
Financial institutions background. 6+ months deep research, 20 enterprise targets profiled, competitive landscape mapped.
Trained on industrial defect taxonomies. Domain expertise in manufacturing quality inspection.
Full-stack/ML for annotation platform, AI pre-labeling, QA automation.
Hire engineer. Build MVP annotation platform.
Launch 2-3 free pilots with enterprise targets.
Convert first paying client. Validate unit economics.
India's $492M annotation market has no industrial specialist. We intend to be that company.