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Training data for AI: annotation, collection and validation

A model learns only from the data it is given. Together with our Israeli partner Keymakr we annotate images, video and 3D, collect and film new datasets, and check every label before it reaches your model. People do the precise work, machines make it faster.

Discuss a project

What we build

  • Image and video annotation

    Bounding boxes, polygons, keypoints and object tracking from frame to frame.

  • 3D point clouds and LiDAR

    Cuboids and segmentation of 3D scenes for self-driving cars and robots.

  • Semantic segmentation

    Pixel-accurate masks for every object and surface in the frame.

  • Data collection and creation

    We find data in your industry or film new datasets from scratch, with actors and on real locations.

  • Data validation

    An independent audit of existing datasets: we find errors, gaps and inconsistent labels.

  • Data for LLMs and agents

    Expert answers, response ranking and dialogues for fine-tuning language models and AI agents.

Where people and machines work together

Annotators, domain experts and film crews prepare the data. Robots, cars and models learn from it.

  1. 01

    Robotics and physical AI

    Spatial data and annotation for robots that move, pick up objects and work next to people.

  2. 02

    Self-driving cars

    Annotated road scenes: cars, trucks, lanes and pedestrians in every frame.

  3. 03

    Datasets filmed from scratch

    When the data you need does not exist, a film crew shoots it in a studio or on location to your scenario.

  4. 04

    Multimodal models

    Image, video and text data for VLM and VLA models that see, understand and act.

What you get

  • Annotation guidelines agreed before work starts
  • A pilot batch on your data to check quality and timing
  • Multi-level quality control with human review
  • Export to COCO, YOLO, Pascal VOC, JSON or your own format
  • Scaling from hundreds to millions of items
  • Work under NDA and in line with GDPR

Technologies

  • Bounding boxes
  • Polygons
  • Keypoints
  • Segmentation
  • LiDAR / 3D
  • Object tracking
  • COCO
  • YOLO
  • RLHF

How a project runs

  1. Discovery

    We study your business, goals and users, then agree on scope, timeline and budget in writing.

  2. Design

    Structure, prototypes and visual design. You see and approve every key screen before development starts.

  3. Development

    Short iterations with regular demos, so progress is visible and changes stay cheap.

  4. Testing and launch

    Functional and device testing, deployment, analytics setup and handover of all accesses.

  5. Support

    Monitoring, updates, fixes and new features under a support agreement.

Tell us about your project

Describe the task in a few sentences. We will get back to you with questions or a first estimate.

Emailoffice@bestsite.az

What happens next

  1. 1We read your requestWe look into the task and ask follow-up questions if needed.
  2. 2We discuss the detailsA call or a short exchange of messages to understand goals, timeline and budget.
  3. 3You get an estimateWe prepare a preliminary estimate of timeline and cost.

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Frequently asked questions

Images, video, 3D point clouds from LiDAR, documents, audio and text. If your data format is unusual, we start with a small pilot.

We write guidelines for every task, run a pilot batch and review the result on several levels. Automatic checks catch obvious errors, and people review the rest.

It depends on the data type, label complexity and volume. We quote after a pilot on your data, so the estimate is based on real numbers.

We work under NDA and follow GDPR requirements. For sensitive projects, annotation can run in an isolated environment.

Didn't find your answer?

Send us a request or an email and we'll answer everything about your project.

Discuss a projectoffice@bestsite.az