Sooner or later every AI team asks whether to build its own labeling team or work with a partner. Both can work. The right answer depends on volume, sensitivity, and how central annotation is to your product.
The Case for In-House
- Full control over process, tools, and priorities
- Deep product context built up over time
- Easier handling of highly sensitive data
The trade-off is cost and focus. Hiring, training, managing, and retaining annotators is a full operation, and demand is rarely steady.
The Case for Outsourcing
- Trained teams available in days, not months
- Capacity that scales up and down with your roadmap
- Established QA processes and tooling
The trade-off is that you depend on the partner’s communication and quality systems, which is why a pilot on your own data matters.
The Hidden Costs
In-house teams carry recruiting, management time, tooling licenses, and idle capacity. Outsourced projects can carry re-work if guidelines are unclear. Compare cost per usable label, not cost per hour.
A Common Middle Path
Many teams keep guideline ownership and final QA in-house while a partner handles volume. You keep the knowledge; they provide the scale.
About Smart Annotahub
Smart Annotahub is a managed data annotation company based in Ha Noi, Viet Nam. Our in-house annotators, QA leads and project managers turn raw image, video, 3D, geospatial, text and audio data into training-ready datasets for teams building computer vision, robotics and language AI. Every project starts with a free pilot, runs on your guidelines and tools, and ships with multi-stage quality checks.
Our Services
Frequently Asked Questions
How does the free pilot work?
Send us a sample of your data and your guidelines. We annotate it at no cost, report accuracy and turnaround, and return a precise quote, usually within a few working days.
How do you ensure annotation quality?
Every batch passes annotator self-checks, peer review and a dedicated QA lead. We agree accuracy targets up front and share QA reports with each delivery.
Can you work in our annotation tool?
Yes. Our team works in your platform or ours and delivers in the formats your pipeline expects, such as COCO, YOLO, Pascal VOC or custom JSON.
How is my data kept secure?
All work is done by our in-house team under NDA, with role-based access and no data leaving approved environments. See our Data Privacy Notice for details.
How is pricing calculated?
Per object, per hour or per project, depending on the task. See Pricing for reference rates, or request a pilot for an exact quote.
Want to see the difference on your own data?
Request Free Pilot
