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Submitted URL: https://pvmldigital.com/
Effective URL: https://pvml.com/
Submission: On April 26 via api from US — Scanned from DE
Effective URL: https://pvml.com/
Submission: On April 26 via api from US — Scanned from DE
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PVML has emerged from stealth mode with an $8 million seed funding round! Read more here. * Home * Product * Our Technology * Solutions * Analyze Data with AI * Data Anonymization * Data Monetization * Resources * Blog * Glossary * FAQ’s * Company * About PVML * Careers * Contact Us Book a Demo Book a Demo THE DATA ACCESS PLATFORM ENGINEERED FOR THE AGE OF AI PVML helps connect, provide access, and secure multiple data sources. We enable enterprises to get live insights from sensitive data by combining AI with our data protection technology. Try Now Your browser does not support the video tag. * * * * * * * * * * * * * * * * * * WHY PVML? Join the paradigm shift in accessing sensitive data. ONE-FITS-ALL COMPLIANCE Eliminate the need for tailored solutions by demonstrating compliance with multiple security frameworks and regulations. Learn more ACCELERATE TIME-TO-INSIGHT Perform real-time, online analytics without worrying about privacy risks. Learn more 3RD PARTY COLLABORATION Enable safe access for third parties without sharing or moving sensitive data. Learn more ENHANCING ACCESS Provide fast and secure access for a broader spectrum of employees. Learn more INTEGRATION WITH AI Use AI to analyze data using free text without sharing sensitive information with AI providers. Learn more LEVERAGE FULL DATA Throw away your anonymization and masking scripts and start harnessing the full data without tagging Personally Identifiable Information (PII). Learn more View all Try Now * ANALYZE DATA WITH AI Users can analyze data using AI to replace complex queries with free text. They can export the results, create graphs, or open the underlying queries for further analysis in a SQL notebook. Learn more Your browser does not support the video tag. * NO GREY AREA Users can ask anything they want – no need to think twice if the question is compliant, PVML does this in real time to make sure users only get the results they’re allowed to see. Learn more Your browser does not support the video tag. * ALL-IN-ONE Analyze data from multiple data sources to create unique analytics flows using SQL notebooks, free text chats and python code. Learn more Your browser does not support the video tag. 01 01 03 * * * Trusted by the most innovative organizations * * * * * * TRUSTED BY Innovative leaders in the data realm, investors, partners and clients. PVML’s unique technology is changing the way companies handle private data. Their concept is simple and intuitive, transformative in value, and encapsulates the complexity under the hood. Gigi Levy-Weiss General Partner at NFX PVML has managed to democratize access to tools that were once considered exclusive only to the largest and most advanced technology companies. Today, PVML tools give every company a capability to leverage sensitive data, redefining the way to navigate use cases such as data anonymization, data sharing, and data monetization. Stan Chudnovsky VP of Messaging, Meta PVML refuses to settle for the status quo; they have a clear vision of a future where data is harnessed responsibly to promote business objectives. Alon Leibovich Managing Director, Intel Ignite PVML’s commitment to responsible data practices aligns perfectly with the demands of my role as a CISO, and their innovative approach positions them as a crucial ally in safeguarding sensitive information and reducing the attack surface. Nir Rothenberg CISO, Rapyd The market is currently missing a comprehensive Differential Privacy solution that can offer more than basic use-cases, and PVML aims to fulfill just that. Ariel Michaeli Head of Israel Investments, Motorola Solutions PVML’s concept allows companies to unlock the full potential of their data, and puts me in a unique position to challenge my executive peers to take a more competitive position on the data we own and be more competitive in the market. Iftach Ian Amit CISO, Investor LATEST BLOG POSTS Explore Our Recent Insights and Updates. * Data Privacy PRESERVING PRIVACY IN AI: ADVANCED STRATEGIES AND SOLUTIONS 'Primum non nocere!' This well-known Latin phrase in medicine means 'first, do no harm.' This principle is crucial because causing damage to one part... 6 min read * Data Privacy WHY DIFFERENTIAL PRIVACY FITS ALL REGULATIONS Nowadays, organizations across industries grapple with the challenge of extracting valuable insights from their data while upholding the highest standards of privacy and compliance... 8 min read * InnovationSoftware THE NEXT-GEN OF DATA ACCESS: LAUNCHING PVML ALONG WITH $8M IN FUNDING 2 years ago I was working as a software engineer at a large corporate. I was part of a team building a product for... 3 min read * Data Privacy GDPR DATA MASKING BEST PRACTICES: A SHIELD FOR PERSONAL INFORMATION In the modern era of digitalization, safeguarding both personal and non-personal information has become essential. Adherence to regulatory standards like the General Data Protection... 15 min read * AITechnology HOW CAN COMPANIES PREVENT AI-BASED RE-IDENTIFICATION ATTACKS? A new powerful form of privacy breach is on the rise, leveraging AI to re-identify individuals based on behavior patterns that can be inferred... 10 min read * Data Privacy 5 BEST PRACTICES FOR SENSITIVE DATA PROTECTION Understanding Sensitive Data Whether you like it or not, every single organization will contain some sort of sensitive data. Back in the day, these used... 7 min read * Data Privacy TOP BENEFITS OF SECURE DATA COLLABORATION You may have heard the phrase “data is the new oil.” This describes the increasing value of data in the modern world, much like... 6 min read * Technology THE IMPACT OF PRIVACY-PRESERVING TECHNOLOGY ON DATA PROTECTION In an era dominated by digital advancements, safeguarding personal data has become paramount. The escalating frequency of data breaches and privacy concerns has prompted... 9 min read * Technology THE DATA ACT AND PPT Which privacy preserving technologies can help share data safely in light of the new Data Act, and how do they do so? On January 11,... 9 min read * AI NAVIGATING DATA PROTECTION IN THE AGE OF AI AI needs data, while people want privacy. AI-based algorithms or models learn how to yield an output for a given input or query by... 7 min read FREQUENTLY ASKED QUESTIONS Everything you need to know. PVML PROVIDES A SECURE FOUNDATION THAT ALLOWS YOU TO PUSH THE BOUNDARIES TL;DR: We allow analytics and ML to be applied on sensitive data, providing mathematically guaranteed private outputs by introducing randomization to the computation. Differential privacy (DP) is a set of systems and practices that help keep the data of individuals safe and private. Differential Privacy offers the strongest possible privacy protection available today, with a mathematical guarantee to back up each algorithm. Differential privacy is achieved by introducing statistical noise. The noise is significant enough to protect the privacy of any individual in the data, but small enough that it will not impact the accuracy of analytics and machine learning methods applied on the data. PVML offers proprietary Differential Privacy technology to exract useful insights and train AI models using datasets containing sensitive information. Our algorithms are performed on the analysis itself, on-the-fly, so that the outputs are privacy-preserving and can be safely used or shared by the user or third-party. Learn more about how we use Differential Privacy HOW IS DIFFERENTIAL PRIVACY DIFFERENT FROM HOMOMORPHIC ENCRYPTION? TL;DR: As opposed to Homomorphic Encryption, Differential Privacy has no overhead in computation and memory cost, and it also guarantees privacy at the output level, preventing reverse engineering and attribute inference attacks. Homomorphic Encryption allows computation directly on encrypted data, however – it isn’t efficient. Because Homomorphic Encryption comes with a large performance overhead, computations that are already costly to do on unencrypted data probably aren’t feasible on encrypted data. Moreover, although the data is unreadable, the computations performed on it remain the same, including the outputs. When outputs are returned in perfect accuracy, the privacy of individuals in the data cannot be guaranteed, and the dataset remains vulnerable to re-identification attacks where sensitive raw data may be extracted in reverse engineering and attribute inference attacks. Read more about Differential Privacy DOES PVML OFFER UNIQUE DIFFERENTIAL PRIVACY CAPABILITIES? TL;DR: PVML prioritizes applicable algorithmic capabilities, beyond what science can currently provide in the field of Differential Privacy. PVML incorporates beyond state-of-the-art research objectives along with software engineering and applied machine learning in order to provide the most efficient Differential Privacy algorithms that produce privacy-preserving results with higher accuracy than existing Differential Privacy solutions. Applicability is our first priority, ensuring that our Differential Privacy algorithms can be seamlessly integrated into a wide range of applications and systems, and without changing the methods, tools or languages you use to interact with data. Whether you are in healthcare, finance, telecommunications, or any other industry, our cutting-edge solutions are designed to safeguard sensitive information while maintaining the utility and integrity of your data. Our commitment to applicability extends to easy deployment, scalability, and adaptability, allowing organizations of all sizes to benefit from state-of-the-art privacy protection without compromising performance. Read more about our Differential Privacy technology HOW DO YOU ADDRESS REGULATORY DEMANDS? TL;DR: PVML has been verified by legal and technological experts in the privacy field. The legislation mandates companies to design their products and processes with privacy in mind, meaning that a company is responsible for ensuring and maintaining the privacy of the personal data it handles. We work alongside a legal team and various security and privacy experts who provide guidance and validation throughout our development process, thereby ensuring that our Differential Privacy algorithms and overall approach maintain individuals’ privacy in accordance with various privacy regulations. Furthermore, we undergo rigorous external audits to ensure that our solution adheres to the highest standards of privacy and security and is SOC2 compliant. Read more about Differential Privacy DO I STILL NEED PVML IF MY DATA DOES NOT CONTAIN ANY IDENTIFIABLE FEATURES? TL;DR: Yes, anonymization is an outdated technique that leaves expensive data value on the table and fails to guarantee privacy, especially in the current age of AI. Yes! Even when removing personally identifiable information (PIIs), the resulting records often include unique combinations of variables and features that might be linked to other publicly available information in order to re-identify specific people or leak sensitive information. In practice, as long as useful information about individuals is included in the data, it is vulnerable to re-identification attacks (and therefore, not anonymous). Moreover, as we transition into an era where data is not only accessed by people but increasingly by advanced AI systems, the risks escalate. AI, being smarter, faster, and exposed to a wealth of information, introduces new challenges to traditional anonymization methods. These intelligent systems can perform intricate attribute inferencing, extracting nuanced insights and patterns that may not be readily apparent to human users. This capability, if exploited by human users, poses significant risks of intentional misuse. Moreover, there’s a potential for unintentional mistakes by AI, leading to inadvertent exposure of sensitive information, further amplifying the challenges in safeguarding data integrity and privacy. Therefore, the evolving landscape of technology requires a comprehensive approach to anonymization to safeguard against risks posed by both human and AI access. PVML’s data protection technology is grounded in mathematics and engineered for the age of AI, ensuring heightened protection against data vulnerabilities and privacy breaches regardless of whether data is accessed by human users, applications, or AI models. Read more about the downfall of anonymization on our blog DO I NEED TO MOVE MY DATA IN ORDER TO USE PVML'S SOLUTION? TL;DR: No. Your sensitive data stays wherever it is located (on-premise / on-cloud) and our platform does not require any duplication or modification of the data. Read more about our deployment and architecture PVML. DATA PEACE OF MIND. Experience the freedom of real-time analytics and the power of data sharing, all while ensuring unparalleled privacy. Book a Demo © 2024 PVML All rights reserved. NAVIGATION * Home * Company * Product * Our Technology * Data Anonymization * Data Monetization * Blog * Glossary * FAQ’s * Careers * Book a Demo * Contact Us SUBSCRIBE TO OUR NEWSLETTER Email* * Terms of Use * Privacy Policy Connect with us * * Website Design & Development InCreativeWeb.com × This website uses cookies This website uses cookies to improve user experience. By using our website you consent to all cookies in accordance with our Cookie Policy. Read more Strictly necessary Performance Targeting Functionality Unclassified Save & Close Accept all Decline all Show details Hide details