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Training Data provides a full cycle of work on marking lidar clouds to create high-quality training datasets

(Light Detection and Ranging)

It uses a laser beam to measure distances to surrounding objects and create a point cloud representing a 3D map of the scene. Labeling LiDAR point clouds involves identifying and classifying objects using data obtained from the LiDAR sensor.



Point Cloud

A point cloud is a set of three-dimensional coordinate points that describe the geometry and location of objects in a scene

3D Object Recognition

Processing of point clouds, three-dimensional models and voxel grids obtained from lidars, stereo cameras or structured light scanners

Terrain modeling

Analysis and processing of data such as altitude maps, laser scans, aerial images to describe the shape and characteristics of the earth's surface and objects

Path Planning and Navigation

Determining the best way to reach the destination, including analysis and consideration of factors: obstacles, road conditions, travel time and user preferences

Change Detection

Detection and classification of changes: deforestation, expansion of buildings, soil erosion, changes in water bodies and other important changes for environmental assessment and management

Virtual Reality and Simulation

Tasks such as gesture recognition, object classification in virtual space, behavioral modeling to develop adaptive responses to user actions

Object Detection

Identification and classification of objects of various types, such as cars, pedestrians, cyclists, buildings, road markings, signs, trees, etc.

Semantic Segmentation

Dividing lidar clouds into small components and determining which classes these components belong to for a deeper understanding of AI systems of the environment

Stages of work

  • Application

    Leave a request on the website for a free consultation with an expert. Th e acco unt manager will guide you on the services, timelines, and price
  • Free pilot

    We will conduct a test pilot project for you and provide a golden set, based on which we will determine the final technical requirements and approve project metrics
  • Agreement

    We prepare a contract and all necessary documentation upon the request of your accountants and lawyers
  • Workflow customization

    We form a pool of suitable tools and assign an experienced manager who will be in touch with you regarding all project details
  • Quality control

    Data uploads for verification are done iteratively, allowing your team to review and approve collected/annotated data
  • Post-payment

    You pay for the work after receiving the data in agreed quality and quantity


  • 24 hours
  • 24 hours
  • 1 to 3 days
  • 1 to 5 days
    Conducting a pilot
  • 1 day to several years
    Carrying out work on the project
  • 1 to 5 days
    Quality control
You pay for the work after you have received the data
in the established quality and quantity

Training Data

  • Quality Assurance:
  • Enhanced Data Accuracy
  • Consistency in Labels
  • Reliable Ground Truth
  • Mitigation of Annotation Biases
  • Cost and Time Efficiency
  • Data Security and Confidentiality:
  • GDPR Compliance
  • Non-disclosure agreement
  • Data Encryption
  • Multiple data storage options
  • Access Controls and Authentication
  • Expert Team:
  • 6 years in industry
  • 35 top project managers
  • 40+ languages
  • 100+ countries
  • 250k+ assessors
  • Flexible and Scalable Solutions:
  • 24/7 availability of customer service
  • 100% post payment
  • $550 minimum check
  • Variable Workload
  • Customized Solutions

Tell us about your project!

    Choose interested services:

    Select an option

    • Data labeling

    • Data collection

    • Datasets

    • Human Moderation

    • Other (describe below)