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By Amar Kanagaraj
In artificial intelligence (AI), especially within natural language processing (NLP), tokenization is a fundamental process that breaks down text into smaller, manageable units known as tokens. Depending on the specific task and model, these tokens can be individual words, subwords, characters, or even symbols.
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By Amar Kanagaraj
Data sharing for offshore testing, development, and other operational needs is often essential in the healthcare industry. Yet, laws governing Protected Health Information (PHI) make this challenging, as sending sensitive data outside the U.S. can introduce significant regulatory risks. To stay compliant, healthcare companies need solutions that can anonymize data without compromising its usability or accuracy.
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By Amar Kanagaraj
APIs are the backbone of modern applications, enabling seamless data exchange between systems. However, the rise of AI agents fundamentally shifts how APIs are utilized. Regular APIs, originally built for deterministic, non-AI use cases, are not inherently designed to handle the complexities and unpredictability of AI-driven applications. Using your regular APIs directly for AI agents or allowing AI agents to integrate without safeguards exposes your systems and data to significant risks.
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By Rahul Sharma
Data tokenization is a critical technique for securing sensitive information by substituting it with non-sensitive tokens. This process plays a crucial role in data protection, especially in industries handling large volumes of personal or financial information. Here, we explore the top data tokenization tools of 2024 to help organizations find the right solutions for protecting their data.
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By Rahul Sharma
As organizations increasingly rely on cloud data platforms, securing PII (Personally Identifiable Information) has become more critical than ever. Snowflake, a robust cloud-based data warehouse, stores and processes vast amounts of sensitive information. With the rise in data breaches and stringent regulations like GDPR and CCPA, safeguarding PII data in Snowflake is essential to ensure data privacy and compliance.
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By Rahul Sharma
The growing reliance on generative AI is transforming industries across the globe. From automating tasks to improving decision-making, the potential of these systems is vast. However, with this progress comes significant risks. Generative AI can be unpredictable, creating new vulnerabilities that expose organizations to data privacy breaches, compliance failures, and other security issues. So, how can companies harness the power of AI while ensuring they remain protected?
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By Rahul Sharma
As artificial intelligence (AI) grows, AI guardrails ensure safety, accuracy, and ethical use. These guardrails are a set of protocols and best practices designed to mitigate risks associated with AI, such as bias, misinformation, and security threats. They are vital in shaping how AI systems, particularly generative AI, are developed and deployed.
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By Rahul Sharma
Deploying large language models (LLMs) securely and accurately is crucial in today’s AI deployment landscape. As generative AI technologies evolve, ensuring their safe use is more important than ever. LLM guardrails are essential mechanisms designed to maintain the safety, accuracy, and ethical integrity of these models. They prevent issues like misinformation, bias, and unintended outputs.
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By Amar Kanagaraj
The integration of AI, especially Gen AI, into healthcare has been transforming the industry, enabling providers to enhance patient care, streamline operations, and reduce costs. Below is an overview of the most promising AI use cases in healthcare that are reshaping the industry.
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By Rahul Sharma
Data protection has become a critical concern worldwide as digital transactions and data exchanges grow. Countries are establishing strict data protection laws to safeguard personal information, and India is no exception. The Digital Personal Data Protection (DPDP) Act is India’s response to growing privacy concerns and the need for robust regulations around personal data usage.
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By Protecto
Welcome to the Protecto Snowflake Integration Demo, where we show you how to safeguard sensitive data using Protecto’s advanced AI-powered masking tools! In today’s world, businesses using Snowflake for AI and analytics face significant risks with sensitive information hidden within unstructured data like comments and feedback columns. Protecto provides a unique solution, precisely masking only the sensitive parts of your unstructured data while leaving the rest untouched, ensuring your datasets remain valuable for analysis.
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By Protecto
Discover how our intelligent data masking solution ensures secure, compliant, and privacy-preserving analytics for your data lakes. Protecto maintains data integrity while empowering your organization to leverage analytics or enable AI/RAG without compromising privacy or regulatory compliance.
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By Protecto
Generative AI is often seen as high risk in healthcare due to the critical importance of patient safety and data privacy. Protecto enables your journey with HIPAA-compliant and secure generative AI solutions, ensuring the highest standards of accuracy, security, and compliance.
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By Protecto
But in the world of gen AI applications, translating and maintaining roles in a vector database is exponentially complex.
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By Protecto
Don't miss out on the critical insights from this exclusive discussion on Gen AI Security and Privacy Challenges in Financial Services brought to you by Protecto!
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By Protecto
Unlock the full potential of Gen AI in finance, without compromising security and privacy. Watch this video for expert advice and cutting-edge solutions.
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By Protecto
Tired of inaccurate LLM (/RAG) responses because of data masking? Generic masking destroys data context, leading to confusion and inaccurate LLM responses. Protecto's advanced masking maintains context for accurate AI results while protecting your sensitive data.
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By Protecto
Introducing Protecto SecRAG, the revolutionary platform that empowers you to launch your own AI assistants/chatbots. No coding is required. Simply connect your existing data sources to Protecto. Our intuitive conversation UI allows you to ask questions about your data in plain English, just like you'd talk to a colleague. SecRAG powers a Telco's contracts bot, a large service providers' talent acquisition co-pilot, a healthcare insurance provider's benefits bot and many more.
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By Protecto
Introducing Protecto's SecRAG, the game-changer for secure AI. SecRAG stands for Secure Retrieval Augmented Generation, a turnkey solution. No need to build complex rag or access controls from scratch. Protecto provides a simple interface and APIs to connect data sources, assign roles, and authorize the data. In a few minutes, your secure AI assistant will be ready. When users ask your Protecto-powered AI assistants, Protecto applies appropriate access control to find the right data and generate responses that don't expose other sensitive information that the user is not authorized to see.
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By Protecto
Know the challenges associated with managing data privacy and security, and the capabilities that organizations need to look for when exploring a data privacy and protection solution.
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By Protecto
Improve your organization's privacy and security posture by automating data mapping. Read on to understand some best practices for privacy compliance.
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By Protecto
Protecto can help improve your privacy and security posture by simplifying and automating your data minimization strategy. Read on to know more.
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Easy-to-use API to protect your enterprise data across the AI lifecycle - training, tuning/RAG, response, and prompt.
Protecto makes all your interactions with GenAI safer. We protect your sensitive data, prevent privacy violations, and mitigate security risks. With Protecto, you can leverage the power of GenAI without sacrificing privacy or security. If you are looking for a way to make your GenAI interactions safer, then Protecto is the solution for you.
Data protection without sacrificing data utility:
- Achieve Compliance And Mitigate Privacy Risks: Preserve valuable information while meeting data retention regulations.
- Embrace Gen AI Without Privacy or Security Risks: Harness the power of Gen AI, ChatGPT, LLMs, and other publicly hosted AI models without compromising on privacy and security.
- Share Data Without Sacrificing Compliance: Comply with privacy regulations and data residency requirements while sharing data with global teams and partners.
- Ensure The Security Of Your Data In The Cloud: Protect your sensitive and personal data in the cloud. Gain control over your cloud data.
- Create Synthetic Data: Harness real-world data for testing without compromising on privacy or security.
- Achieve Data Retention Compliance with Anonymisation: Simplify compliance efforts and safeguard sensitive data.
Protect your enterprise data across the AI lifecycle.