The people behind the labels

A model is only as good as the labels it learns from. At NextAI Pros, those labels are made by people. Our annotators and project managers turn raw images, video and text into training data you can trust.

The team in numbers

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50,000+ vehicle images labelled — and counting.

At NextAI Pros, we fuel the future of artificial intelligence with high-quality, scalable data annotation. We specialize in delivering the precise, reliable training datasets your machine learning models need to thrive across any industry.

Featured Experts

Our labels are made by people. A founder leads the team, project managers run the day-to-day work, and trained annotators do the labelling. Each group has a clear job, and each one matters.

Project managers turn a brief into clear instructions. Annotators follow those instructions, item by item. And every batch is checked before it leaves. Here is who does what.

Founder

image annotation video annotation quality review project leadership

The founder leads NextAI Pros and sets the standard for how work is done. Every project starts with a clear brief, agreed label classes and a quality bar the team must meet. The founder works with the project managers on guidelines, schedules and delivery, so every client has one clear point of contact from the first message to the final files.

8 Project Managers

guidelines scheduling client contact quality review

Project managers run the guidelines, the schedule and the client contact. They turn a client’s brief into clear instructions for the annotators, check progress every day and review work before it leaves. If a label is unclear, they ask the client — they do not guess.

30+ Annotators

image annotation video annotation text annotation quality review

Annotators label the data. They work on bounding box, polygon, semantic segmentation, keypoint detection, image classification and object tracking, across image, video and text. Every annotator is trained before they start, and every batch passes three-stage QA.

What the Team Labels

Real data annotation projects at NextAI Pros labelling images for self-driving car AI training

In general terms, annotators work on bounding box, polygon, semantic segmentation, keypoint detection, floorplan and blueprint annotation, medical image labeling, and video annotation.
Tools used by the team include CVAT, Roboflow, Label Studio, LabelMe and Supervisely. Exports include COCO JSON, YOLO and Pascal VOC.
Every batch passes three-stage QA, with corrections before delivery, targeting 98%+ accuracy. See our services, image annotation and video annotation.

Tools the team uses every day

The team sets up the annotation tools for each project and works in CVAT, Roboflow, Label Studio, LabelMe and Supervisely. Labelled data is delivered in the formats your model needs — COCO JSON, YOLO and Pascal VOC — with documentation and a short guide. If a label is unclear, the team asks the client. It does not guess.

Our Vetting & Quality Assurance Process

How we guarantee quality

Trained annotators

Every annotator is trained before they start work. Training covers the annotation tools, the label classes and the guidelines for each project, so labels are consistent from the first batch to the last.

Three-stage QA

Every batch passes three-stage QA. First the annotators self-check their work. Then a QA specialist reviews it against the guidelines. Then it is checked again before delivery. Each stage can send work back.

Specialist checks

Specialist checks look at the work of each annotator against the guidelines. A second pair of eyes catches edge cases early, before small mistakes reach the full batch.

Corrections before delivery

Corrections are made before delivery, not after. If a label is wrong or a guideline is not followed, the batch is fixed and checked again. A client does not receive unchecked work.

Our Services

Image Annotation

Image annotation by NextAI Pros with bounding boxes on labelled street images for AI training data
Bounding box, polygon, segmentation and keypoint labels for images, blueprints and floor plans.

Video Annotation

Video annotation by NextAI Pros labelling sports video frames and tracking players for AI training
Frame-by-frame labels and object tracking for video, ready for your model.

Text Annotation

Text annotation by NextAI Pros labelling financial reports and documents for AI training data
Labels for documents, sentences and text, with quality checks before delivery.

All Services

Image, video and text annotation — one team, one quality bar, one point of contact.

How Your Data Flows Through the Team

1. Understanding the Need

We begin with an open discussion. We learn your project goals, the type of data you have, and the level of detail your labels need.

2. Tailored Data Annotation Plan

Based on your requirements, we design a custom action plan. It covers label classes and examples, key edge cases, and the quality checks for the work.

3. Annotation Tool Setup

We set up the tools for your project, ready to handle volume. We work in CVAT, Roboflow, Label Studio, LabelMe and Supervisely.

4. Execution by Skilled Annotators

Our expert annotators label the data, one image, video frame or document at a time. They follow the plan and the guidelines for every item.

5. Ensuring Quality Through Rigorous QA

Every batch passes three-stage QA against a 98%+ accuracy target. A QA specialist reviews each batch against the guidelines, and corrections are made before delivery.

6. Seamless Delivery

We deliver in the formats you need, such as COCO JSON, YOLO and Pascal VOC, with documentation and a clear file structure. If a format is not listed, ask us.

Ready to Put Our Team to Work on Your Project?

Send your data type, label classes, rough volume and deadline. A project manager will reply about the next step. Email info@nextaipros.com or use the contact page.

Frequently asked questions about our data annotation team

Who is on the NextAI Pros data annotation team?

The team is led by the founder, with 8 project managers running the guidelines, schedule and client contact, and 30+ trained annotators labelling images, video and text. Every annotator is trained before they start work.

The team labels images, video, text, audio and LiDAR data — bounding boxes, polygons, semantic segmentation, keypoint detection, object tracking, floorplan and blueprint annotation, and medical image labelling.

Every batch passes three-stage QA: annotators self-check their work, then a QA specialist reviews it against the guidelines, and it is checked again before delivery. Corrections are made before delivery, never after.

The team works in CVAT, Roboflow, Label Studio, LabelMe and Supervisely, and delivers labelled data as COCO JSON, YOLO or Pascal VOC, with documentation and a short guide.

A project manager owns your guidelines, schedule, client contact and delivery. The founder works with project managers on guidelines, schedules and delivery. If a label is unclear, the team asks the client — it does not guess.

Send your data type, label classes, rough volume and deadline through the contact page or by emailing info@nextaipros.com. A project manager will reply about the next step.