Visual Layer Description
Visual Layer is a production-grade platform built for teams handling image and video datasets at scale. It enables direct interaction with visual data—searching, filtering, labeling, and analyzing—without needing custom scripts or manual sorting. Originally developed by the creators of Fastdup, it extends the same deduplication capabilities into full dataset workflows.
Designed to be infrastructure-agnostic, Visual Layer can run entirely on-premise, in the cloud, or embedded via API. It's model-agnostic too, making it useful for debugging, cleaning, or pretraining tasks in any ML pipeline. The system flags anomalies, catch mislabeled frames, and surfaces diverse subsets to improve generalization and reduce noise.
It fits into existing pipelines without requiring migration or vendor lock-in, and supports engineers and ops teams alike.
Visual Layer Alternatives
Ango Hub
Ango Hub is an all-in-one, quality-oriented data annotation platform that AI teams can use. Ango Hub is available on-premise and in the cloud. It allows AI teams and their data annotation workforces to quickly and efficiently annotate their data without compromising quality.
Ango Hub is the only data annotation platform that focuses on quality. It features features that enhance the quality of your annotations. These include a centralized labeling system, a real time issue system, review workflows and sample label libraries. There is also consensus up to 30 on the same asset.
Ango Hub is versatile as well. It supports all data types that your team might require, including image, audio, text and native PDF. There are nearly twenty different labeling tools that you can use to annotate data. Some of these tools are unique to Ango hub, such as rotated bounding box, unlimited conditional questions, label relations and table-based labels for more complicated labeling tasks.
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Lenso.ai
Lenso.ai, a tool for AI image searches, allows you to search for images based on your interests. Lenso.ai uses advanced AI technology to allow you to search for images, places, people, duplicates and related images.
Lenso.ai reverse image search is more accurate and efficient than traditional image searches. Lenso.ai, an AI-powered reverse imaging tool, analyzes the image you are searching for quickly, identifying only the best matches. Searching by image is easy with lenso.ai, and it doesn't require any special skills or knowledge.
Reverse image search is designed to fit diverse needs, whether you're a professional photographer looking for different places/landscapes/landmarks, a marketer searching for related or similar images, an enthusiast exploring the duplicates/copyright or you want to protect your privacy using face search.
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Voxel51
FiftyOne, developed by Voxel51, stands out as a leading platform for visual AI and computer vision data management.
The effectiveness of even the most advanced AI models diminishes without adequate data, which is why FiftyOne empowers machine learning engineers to thoroughly analyze and comprehend their visual datasets, encompassing images, videos, 3D point clouds, geospatial information, and medical records.
With a remarkable count of over 2.8 million open source installations and an impressive client roster that includes Walmart, GM, Bosch, Medtronic, and the University of Michigan Health, FiftyOne has become an essential resource for creating robust computer vision systems that function efficiently in real-world scenarios rather than just theoretical environments.
FiftyOne enhances the process of visual data organization and model evaluation through its user-friendly workflows, which alleviate the burdensome tasks of visualizing and interpreting insights during the stages of data curation and model improvement, tackling a significant obstacle present in extensive data pipelines that manage billions of samples.
The tangible benefits of employing FiftyOne include a notable 30% increase in model accuracy, a savings of over five months in development time, and a 30% rise in overall productivity, highlighting its transformative impact on the field.
By leveraging these capabilities, teams can achieve more effective outcomes while minimizing the complexities traditionally associated with data management in machine learning projects.
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Google Cloud Natural Language API
Leverage advanced machine learning techniques for thorough text analysis that can extract, interpret, and securely store textual data. With AutoML, you can create top-tier custom machine learning models effortlessly, without writing any code. Implement natural language understanding through the Natural Language API to enhance your applications. Utilize entity analysis to pinpoint and categorize various fields in documents, such as emails, chats, and social media interactions, followed by sentiment analysis to gauge customer feedback and derive actionable insights for product improvements and user experience. The Natural Language API, combined with speech-to-text capabilities, can also provide valuable insights from audio sources. Additionally, the Vision API enhances your capabilities with optical character recognition (OCR) for digitizing scanned documents. The Translation API further enables sentiment understanding across diverse languages. With custom entity extraction, you can identify specialized entities within your documents that may not be recognized by standard models, saving both time and resources on manual processing. Ultimately, you can train your own high-quality machine learning models to effectively classify, extract, and assess sentiment, making your analysis more targeted and efficient. This comprehensive approach ensures a robust understanding of textual and audio data, empowering businesses with deeper insights.
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Pricing
Pricing Starts At:
$200/month
Pricing Information:
Final pricing depends on several factors, including:
The format and resolution of your data
Total dataset size (duration and storage)
Infrastructure preference (e.g. Cloud vs. On-Demand instances)
And other possible circumstances and details
The format and resolution of your data
Total dataset size (duration and storage)
Infrastructure preference (e.g. Cloud vs. On-Demand instances)
And other possible circumstances and details
Free Version:
Yes
Free Trial:
Yes
Company Details
Company:
Visual Layer
Year Founded:
2022
Headquarters:
Israel
Website:
visual-layer.com
Media
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Product Details
Platforms
Web-Based
On-Premises
Types of Training
Training Docs
Training Videos
Customer Support
Online Support
Visual Layer Features and Options
Visual Search Software
Barcode Recognition
Catalog Management
Customer Activity Tracking
Filtering
IP Protection
Image Tagging
Mobile App
Optical Character Recognition
Product Recommendations
Product Search
Reverse Image Search
Video Search
Computer Vision Software
Blob Detection & Analysis
Building Tools
Image Processing
Multiple Image Type Support
Reporting / Analytics Integration
Smart Camera Integration
Artificial Intelligence Software
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)
Qualitative Data Analysis Software
Annotations
Collaboration
Data Visualization
Media Analytics
Mixed Methods Research
Multi-Language
Qualitative Comparative Analysis
Quantitative Content Analysis
Sentiment Analysis
Statistical Analysis
Text Analytics
User Research Analysis
Visual Layer User Reviews
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