Protecto

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Protecto is an AI Data Security & Privacy platform trusted by enterprises across healthcare and BFSI sectors. We help organizations detect, classify, and protect sensitive data in real-time AI workflows while maintaining regulatory compliance with DPDP, GDPR, HIPAA, and other frameworks. Founded in 2021, Protecto is headquartered in the US with operations across the US and India.
  • AI Privacy, AI Security, AI Trust

Regulatory Compliance & Data Tokenization Standards

As we move deeper into 2025, regulatory expectations are rising, AI workloads are expanding rapidly, and organizations are under pressure to demonstrate consistent, trustworthy handling of personal data. Learn how tokenization reduces risk, simplifies compliance, and supports scalable data operations. ...
  • 7 min read
privacy first versus privacy later
  • AI Privacy

Privacy First vs. Privacy Later: The Cost of Delaying in the AI Era

In the AI era, delayed privacy turns into compounding technical debt, regulatory exposure, and brittle systems that are painful to unwind. This post breaks down why privacy-first design is no longer optional, and what it really costs when teams wait....
  • 5 min read
Overcoming the Challenges and Limitations of Data Tokenization
  • AI Privacy, AI Security

Overcoming the Challenges and Limitations of Data Tokenization

Analyze the most pressing challenges and known limitations in data tokenization, from technical hurdles to process complexity and scalability. Gain solutions and mitigation strategies to ensure effective and secure data protection deployments....
  • 8 min read
Best Practices for data tokenization
  • AI Privacy, AI Security, AI Trust

Best Practices for Implementing Data Tokenization

Discover the latest strategies for deploying data tokenization initiatives effectively, from planning and architecture to technology selection and integration. Detailed checklists and actionable insights help organizations ensure robust, scalable, and secure implementations....
  • 5 min read
types of data tokenization
  • AI Guardrails

Types of Data Tokenization: Methods & Use Cases Explained

Explore the different types of data tokenization, including commonly used methods and real-world applications. Learn how each type addresses specific data security needs and discover practical scenarios for choosing the right tokenization approach....
  • 5 min read
Advanced Data Tokenization
  • AI Privacy

Advanced Data Tokenization: Best Practices & Trends 2025

Enterprises face growing risks from uncontrolled PII spread. This blog explores practical approaches to limit data proliferation, including tokenization, centralized identity models, and governance strategies that strengthen compliance, reduce exposure, and ensure secure handling of sensitive information across systems....
  • 11 min read
DPDP vs GDPR. What Indian Enterprises Actually Need to Know
  • AI Privacy, Data Compliance, Data Privacy

DPDP vs GDPR: Key Differences for Indian Enterprises

Your company is subject to at least three data privacy frameworks. Here's how they differ, why they conflict, and what you should prioritize first. especially if you're deploying AI....
  • 10 min read
user consent llm privacy
  • AI Privacy

Why User Consent Is Revolutionizing LLM Privacy Practices

Explore the pivotal role of user consent in the future of LLM privacy. This article covers new consent management strategies, best practices for transparency, and how robust user consent policies are transforming ethical AI and regulatory compliance....
  • 7 min read
  • AI Compliance, AI Privacy, AI Security

Understanding the Impact of AI on User Consent and Data Collection

Explore how AI transforms user consent and data collection, emphasizing the need for clearer, ongoing, and granular consent. Understand legal expectations, privacy-by-design strategies, and practical frameworks to ensure ethical, transparent, and compliant AI data practices at scale....
  • 11 min read
How To Ensure Data Privacy With AI: A Step-by-Step Guide
  • AI Privacy

How to Ensure Data Privacy with AI: A Step-by-Step Guide

This article offers a step-by-step guide to achieving LLM privacy compliance in 2025. It emphasizes privacy-by-design, data minimization, and audit readiness, helping organizations secure AI workflows from ingestion to deletion while meeting evolving regulatory and ethical standards....
  • 8 min read
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