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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

SKY ENGINE AI provides a unified Synthetic Data Cloud designed to power next-generation Vision AI training with photorealistic 3D generative scenes. Its engine simulates multispectral environments—including visible light, thermal, NIR, and UWB—while producing detailed semantic masks, bounding boxes, depth maps, and metadata. The platform features domain processors, GAN-based adaptation, and domain-gap inspection tools to ensure synthetic datasets closely match real-world distributions. Data scientists work efficiently through an integrated coding environment with deep PyTorch/TensorFlow integration and seamless MLOps compatibility. For large-scale production, SKY ENGINE AI offers distributed rendering clusters, cloud instance orchestration, automated randomization, and reusable 3D scene blueprints for automotive, robotics, security, agriculture, and manufacturing. Users can run continuous data iteration cycles to cover edge cases, detect model blind spots, and refine training sets in minutes instead of months. With support for CGI standards, physics-based shaders, and multimodal sensor simulation, the platform enables highly customizable Vision AI pipelines. This end-to-end approach reduces operational costs, accelerates development, and delivers consistently high-performance models.

Description

VeloView is a versatile open-source platform tailored for the real-time visualization and analysis of 3D LiDAR data obtained from various Velodyne HDL sensor models, such as the HDL-64E, HDL-32E, VLP-32, VLP-16, Puck, Puck LITE, Puck Hi-Res, Ultra Alpha, Alpha Prime, Velarray, Velabit, and Veladome. This application allows users to either visualize live data streams or review previously recorded data archived in .pcap files, while also offering the functionality to record live streams for future examination. With tools designed for displaying, selecting, and measuring data from captured points, VeloView supports custom color maps influenced by factors such as intensity-of-return, time, distance, azimuth, dual return type, and laser ID. Users have the option to export data in CSV format as XYZ coordinates or capture screenshots of the point cloud visualization. Recent enhancements have added features like compatibility with Velarray sensors, the ability to operate multiple sensors concurrently, and independent transformation of live data for each sensor, thereby expanding its usability and versatility. Overall, VeloView stands out as a powerful tool for professionals working with 3D LiDAR technology.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Google Sheets
Kitware Glance
Microsoft Excel

Integrations

Google Sheets
Kitware Glance
Microsoft Excel

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

SKY ENGINE AI

Founded

2018

Country

United Kingdom

Website

www.skyengine.ai

Vendor Details

Company Name

Kitware

Founded

1998

Country

United States

Website

www.paraview.org/veloview/

Product Features

Artificial Intelligence

Chatbot
For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)

Computer Vision

Blob Detection & Analysis
Building Tools
Image Processing
Multiple Image Type Support
Reporting / Analytics Integration
Smart Camera Integration

Deep Learning

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

Virtual Reality

Application Development
Augmented / Mixed Reality
Collaboration
Content Creation
Cross-Device Publishing
Drag & Drop
Immersive Training
Process Simulation
Product Visualization
Social Sharing
User Interaction Tracking
Virtual Meetings
Virtual Prototyping

Product Features

Alternatives

Alternatives

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