Training Tomorrow's AI
with Human-Led Precision.
Your Strategic Outsourcing Partner
• Build models with better precision
• Label multi-modal datasets at scale
• Control QA and avoid hallucinations
• Ensure annotation security and bias audits
The problem?
Task Type | Examples | Price Range |
Image/Video | Object tagging, bounding boxes, polygons, semantic segmentation | $0.02–$0.10/image |
Text/NLP | Entity recognition, sentiment analysis, classification, prompt scoring | $0.03–$0.08/text unit |
Audio | Speaker ID, intent detection, transcription, classification | $0.06–$0.15/audio min |
Medical/Finance Datasets | ICD coding, billing QA, financial document tagging | $0.08–$0.20/item |
QA-as-a-Service | Multi-stage QA, flagging, and reporting | $300–$700/month |
Full RLHF Workflows | Prompt evaluation, hallucination flagging, preference ranking | — |
In-house data team (US/EU)
$8,000/month for 2 annotators + infrastructure overhead
Nezda team (PH)
$1,200/month per annotator + bundled QA
Savings
$5,000–$10,000 per model phase
Time to scale
2–3 days vs. 4–6 weeks hiring delay
4. Weekly reports with error breakdowns
1. Medical and finance labeling expertise
3. Prompt scoring and LLM evaluation
5. Trained Philippine workforce
7. Flexible pricing by geography
Case Studies
US AI Startup
→ 50,000+ medical image tags
UAE Voice AI Company
EU FinTech
Power Your AI Model with Human Accuracy.