Industrial AI data operations for computer vision, robotics and 3D/sensor systems
Training and validation datasets, managed annotation and QA, plus ongoing human review of model outputs across image, video, tracking, segmentation, point clouds and sensor data
DISCUSS A PROJECT How Does It Work?
Send us your task and sample data
Describe what needs to be labeled or reviewed and, if possible, share a representative sample of the data
Confirm the workflow and pilot
We agree on guidelines, QA criteria, output format, timeline and pricing before production
Scale production and receive validated data
We run the workflow with managed QA and deliver in agreed batches or as an ongoing data operation
Real Example
"Please label and categorize walls, rooms, and furniture using bounding boxes."
Extract from the corresponding JSON file:
{
"annotations": [
{
"id": "2ea57c70-60cf-4321-9424-ca0728cac0f5",
"class": "sink",
"type": "box",
"angle": 0,
"coordinates": { "x": 991, "y": 478, "w": 82, "h": 80 }
},
...
]
}This is a simple example; we also support video, tracking, segmentation, point clouds and other 3D/sensor data.
Prominent Clients Include
Frequently Asked Questions
We combine managed human annotation with engineering-led workflow design and strict QA. This is especially useful for industrial computer-vision and robotics teams that need reliable datasets and repeatable data workflows without building an annotation operation in-house.
Pilot batches can often be started quickly. Full timelines depend on dataset size, task complexity and QA requirements. We agree delivery milestones before production and can work batch-by-batch for ongoing datasets.
We can handle domain-specific tasks when a reviewer can follow clear instructions and examples. If a decision requires deep subject-matter expertise, we can structure the workflow so ambiguous cases are escalated to your domain experts rather than guessed by annotators.
Yes. We use our own tools and a trusted pool of human annotators.
Payment terms depend on project size. Smaller projects are typically 50% upfront and 50% on completion; larger or ongoing projects can be billed batch-by-batch or by agreed milestones.
There is no fixed minimum or maximum. We handle pilot batches as well as larger and recurring workloads.
We commonly deliver JSON, but we can support other formats and adapt the output structure to your existing training or evaluation pipeline.
Still Have Questions?
Do not hesitate to drop us an e-mail at contact@annotateai.co
About Us
Our team consists of software engineers, researchers and a trusted pool of human annotators. We combine human annotation, in-house tooling and strict QA and acceptance methodology to support image, video and 3D/sensor datasets. For perception, 3D and field engineering beyond the dataset, visit MIVAR.
Graduated from Y Combinator Startup School W2020
Copyright © 2026 Annotate AI (trade name) - All Rights Reserved.
Nexcentu Technologies Limited.
contact@annotateai.co
Nexcentu Technologies Limited.
contact@annotateai.co