AI Data Annotation & Labeling. Ground truth.
Training data labeled by people who know what they are looking at. Get high-quality, expertly labeled training datasets that make your AI models more accurate and reliable.
Book a Fusion WorkshopThe spec.
The build, stage by stage. This is what the design phase papers and prices.
You own the build. The workflow, the integrations, and the credentials live in your accounts, not ours. Documented, handed over, yours.
Fixed price. Fixed date.
The walk-away: If automation will not pay for itself in your operation, we say so at the workshop, and you keep the map.
What we need from you: a decision-maker in the workshop, system access by week one, and honest answers about how the work really flows.
Adjacent builds.
Most engagements expand into one of these after the first build proves out.
AI Chatbots and Virtual Assistants·Workflow Automation·AI-Powered CRM Systems·Document Processing and OCR·Predictive Analytics
Straight answers.
What types of data can you annotate?
We handle all major data types for AI training: image annotation (bounding boxes, segmentation masks, keypoints, classification), text annotation (sentiment, entity recognition, intent classification, summarization), document annotation (information extraction, table recognition, layout analysis), audio annotation (transcription, speaker diarization, emotion detection), and video annotation (object tracking, action recognition, temporal segmentation). If your data type is not listed here, reach out, we have likely worked with it or can develop an annotation workflow for it.
How do you ensure annotation quality and consistency?
Quality control is built into every step of our process. We start with detailed annotation guidelines co-developed with your team. Annotators are trained on your specific domain before beginning work. Every annotation is reviewed by a second annotator, and disagreements are resolved by a senior reviewer. We track inter-annotator agreement metrics continuously and retrain annotators when consistency drops. Random samples are audited by our quality team, and we provide transparent quality reports with every delivered dataset. Our target is 95%+ annotation accuracy on every project.
How much does data annotation cost?
Costs vary based on data type, annotation complexity, volume, and required expertise level. Simple image classification might cost $0.02-0.10 per image, while complex segmentation or medical annotation can range from $0.50-5.00 per image. Text annotation typically costs $0.05-0.50 per document depending on complexity. We provide detailed pricing after reviewing sample data and annotation requirements. For most AI projects, the total annotation cost is a small fraction of the overall model development budget and has an outsized impact on model quality.
Can you handle sensitive or confidential business data?
Yes. We implement strict data security protocols for all annotation projects. This includes NDA agreements with all annotators, secure annotation platforms with access controls and audit logging, encrypted data transfer and storage, and compliance with relevant regulations like HIPAA for healthcare data. For highly sensitive data, we offer dedicated annotation teams who work exclusively on your project in controlled environments. We can also set up on-premise annotation workflows where your data never leaves your systems.