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What is PII Anomalyzer?
PII Anomalyzer is a dedicated desktop application crafted to detect, anonymize, and redact personally identifiable information (PII) in documents, employing a unique dual-model AI system that functions entirely offline. This software is especially advantageous for professionals in legal, healthcare, finance, and compliance fields who prioritize confidentiality and cannot afford to share sensitive information with external cloud services or public AI platforms.
Notable features include:
- Support for a wide range of PII entity types, including names, Social Security numbers, financial account numbers, medical identifiers, addresses, dates, and customizable patterns.
- Four different de-identification techniques: Redact, Replace, Highlight, and Mask.
- Proprietary dual-model AI that delivers enhanced accuracy relative to conventional single-model alternatives.
- Compatibility with various file formats such as native and scanned PDFs, DOCX, XLSX, XLS, XLSM, XLSB, and plain text files.
- Built-in optical character recognition (OCR) capabilities for the effective processing of scanned documents.
- A re-identification mode that enables users to restore contextual information from AI outputs, contractor submissions, or reviewer feedback.
- The capacity to handle multiple documents simultaneously for improved efficiency.
By operating completely offline, the software guarantees that no telemetry is sent, ensuring that all data remains securely stored on your device.
Offered at a price of $249 annually, it includes a 7-day free trial and is compatible with both Windows and macOS, making it a flexible option for organizations committed to safeguarding sensitive information. Additionally, regular updates and customer support enhance the overall user experience, further solidifying its value for those handling PII.
What is Macgence?
We have made significant progress in the AI value chain through numerous projects that integrate a wide array of data types, industries, and geographical areas. Our broad and diverse experiences enable us to effectively address specific challenges and improve solutions across various sectors. We deliver precision-crafted custom data sources that are designed to meet the unique needs of your model from different locations, all while maintaining rigorous compliance with GDPR, SOC 2, and ISO standards. Our data annotation and labeling services boast an exceptional accuracy rate of approximately 95% across all data forms, ensuring optimal performance for your models. During the early phases of development, assess your model's capabilities to receive an unbiased expert evaluation of crucial performance indicators such as bias, duplication, and ground truth responses. Furthermore, enhance the precision of your model by leveraging the skills of our dedicated validation team to verify and fine-tune your model's outputs for even better outcomes. This all-encompassing strategy guarantees that your AI solutions are not only effective but also ethical and dependable, paving the way for long-term success in the dynamic field of artificial intelligence. By prioritizing these principles, we aim to foster innovation while ensuring accountability in our methodologies.
Integrations Supported
Additional information not provided
Integrations Supported
Additional information not provided
API Availability
API Availability
Pricing Information
$249/year (7-day free trial)
Free Trial Offered?
Pricing Information
Pricing not provided
Supported Platforms
Windows
Mac
Supported Platforms
SaaS
Customer Service / Support
Web-Based Support
Customer Service / Support
Web-Based Support
Training Options
Documentation Hub
Training Options
Documentation Hub
On-Site Training
Company Facts
Organization Name
Southwest Management Technology
Date Founded
2000
Company Location
United States
Company Website
www.piianomalyzer.ai/
Company Facts
Organization Name
Macgence
Date Founded
2022
Company Location
India
Company Website
macgence.com
Categories and Features
Data De-Identification
Not specified
Categories and Features
Content Moderation
Not specified
Data Annotation
Not specified
Data De-Identification
Not specified
Data Validation
Not specified