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features
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support

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Description

As facial recognition technology advances, the collection of public video footage poses significant privacy threats. Brighter AI's Precision Blur stands out as the leading solution for accurate face redaction globally. Their innovative Deep Natural Anonymization leverages generative AI to generate synthetic face overlays that ensure individuals remain unrecognizable, all while maintaining the quality necessary for machine learning applications. The Selective Redaction interface empowers users to choose which personal information in videos to anonymize selectively. In specific scenarios, like those encountered in media and law enforcement, it may not be necessary to blur every face. Following automated detection processes, users have the option to individually select or deselect objects. Furthermore, the Analytics Endpoint delivers essential metadata linked to the original elements, including bounding box coordinates, facial landmarks, and attributes of individuals. With JSON outputs, users can access pertinent information while ensuring that images or videos remain compliant and anonymized, preserving privacy in an increasingly digital world. This combination of features not only enhances privacy but also supports various professional applications effectively.

Description

Protecting your personal information is crucial, and it’s essential to create data that appears genuine for software development purposes. To achieve this, DOT Anonymizer provides a solution that effectively masks your testing data while maintaining its consistency across various data sources and database management systems. The risk of data breaches arises significantly when using personal or identifiable information in non-production environments such as development, testing, training, and business intelligence. With the growing number of regulations worldwide, organizations are increasingly required to anonymize or pseudonymize sensitive information. This process allows you to keep the original format of the data while your teams can operate with believable yet fictional datasets. It is vital to manage all your data sources effectively to ensure their continued utility. You can easily invoke DOT Anonymizer functions directly from your applications, ensuring consistent anonymization across all database management systems and platforms. Additionally, it’s important to maintain relationships between tables to guarantee that the data remains realistic. The tool is capable of anonymizing a variety of database types and file formats, including CSV, XML, JSON, and more. As the demand for data protection grows, utilizing a solution like DOT Anonymizer becomes increasingly essential for maintaining the integrity and confidentiality of your data.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Azure Cosmos DB
Couchbase
Elasticsearch
H2
IBM Db2
IBM Informix
JSON
MariaDB
MongoDB
MySQL
Oracle Cloud Infrastructure
PostgreSQL
SQL Server
Salesforce
XML

Integrations

Azure Cosmos DB
Couchbase
Elasticsearch
H2
IBM Db2
IBM Informix
JSON
MariaDB
MongoDB
MySQL
Oracle Cloud Infrastructure
PostgreSQL
SQL Server
Salesforce
XML

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

€488 per month
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

Brighter AI Technologies

Country

Germany

Website

brighter.ai

Vendor Details

Company Name

DOT Anonymizer

Country

United States

Website

www.dot-anonymizer.com/data-masking/dot-anonymizer/

Product Features

Deep Learning

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

Alternatives

Alternatives

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