Protecting Data Privacy in the Age of AI: Patented.ai Secures $4M in Pre-Seed Funding to Fortify Data Security

In a move to address the growing concerns around data privacy and confidentiality in artificial intelligence (AI), Patented.ai, a San Francisco-based startup, has secured $4 million in pre-seed funding. The investment will boost the development and expansion of their groundbreaking on-device solution, LLM Shield. With LLM Shield, organizations can protect sensitive information from being accessed, analyzed, or stored by large language models (LLMs).

Problem Statement

Artificial intelligence has undoubtedly revolutionized productivity across various industries. However, as we increasingly rely on AI models that learn from vast amounts of data, the risk to data privacy and confidentiality becomes a significant concern. This has led to the emergence of disruptive solutions aimed at protecting sensitive data from falling into the wrong hands, such as Patented.ai’s LLM Shield.

Solution Overview

LLM Shield, the flagship product developed by Patented.ai, provides an effective defense mechanism against data leakage and unauthorized access. This on-device solution scans the text input box of LLMs to filter out personally identifiable information (PII), trade secrets, and other sensitive data before it can be intercepted or stored. One of the pivotal aspects of the solution is its ability to encrypt sensitive data, ensuring its security both during transit and at rest. By encrypting the information, LLM Shield adds an extra layer of protection against potential breaches or unauthorized access. This enables organizations to confidently leverage AI technology without compromising the privacy and confidentiality of their data.

Expansion Plans

With the infusion of funding, Patented.ai aims to enhance the capabilities of LLM Shield, focusing primarily on the enterprise segment. By bolstering the solution’s features and scalability, the company aims to cater to the diverse needs of organizations handling large volumes of sensitive data. Patented.ai also recognizes the importance of safeguarding individuals’ personal information from LLMs. In addition to the enterprise version, the company offers a free personal edition of LLM Shield. This version allows individuals to protect their personal data from LLMs on up to three devices, ensuring that even on a personal level, privacy is maintained.

Importance of Data Privacy in AI

According to Wayne Chang, the Founder of Patented.ai, while AI offers unparalleled productivity and efficiency benefits, it also poses significant risks to data privacy and confidentiality. With the increased proliferation of AI models and the potential for large-scale data breaches, organizations and individuals need robust solutions like LLM Shield to mitigate these risks and maintain control over their sensitive information.

Funding Details

Patented.ai’s recent funding round was led by Cooley LLP, a prominent venture capital firm, along with participation from several angel investors. Their support highlights the recognition of the pressing need for data protection solutions in the AI industry.

Implementation Details

Deploying LLM Shield is a straightforward process. It can be easily installed using existing endpoint management solutions, minimizing any disruption to organizational workflows. Moreover, LLM Shield is compatible with both Windows and macOS operating systems, allowing for seamless integration across various devices and platforms.

As the AI industry continues to evolve and permeate different sectors, the importance of safeguarding sensitive data cannot be overstated. Patented.ai’s successful pre-seed funding round and the innovative LLM Shield solution mark a significant step towards addressing the potential threats to data privacy and confidentiality. By enabling organizations and individuals to protect their information from unauthorized access and data leaks, Patented.ai is playing a vital role in shaping a more secure AI landscape.

Explore more

Trend Analysis: AI in Real Estate

Navigating the real estate market has long been synonymous with staggering costs, opaque processes, and a reliance on commission-based intermediaries that can consume a significant portion of a property’s value. This traditional framework is now facing a profound disruption from artificial intelligence, a technological force empowering consumers with unprecedented levels of control, transparency, and financial savings. As the industry stands

Insurtech Digital Platforms – Review

The silent drain on an insurer’s profitability often goes unnoticed, buried within the complex and aging architecture of legacy systems that impede growth and alienate a digitally native customer base. Insurtech digital platforms represent a significant advancement in the insurance sector, offering a clear path away from these outdated constraints. This review will explore the evolution of this technology from

Trend Analysis: Insurance Operational Control

The relentless pursuit of market share that has defined the insurance landscape for years has finally met its reckoning, forcing the industry to confront a new reality where operational discipline is the true measure of strength. After a prolonged period of chasing aggressive, unrestrained growth, 2025 has marked a fundamental pivot. The market is now shifting away from a “growth-at-all-costs”

AI Grading Tools Offer Both Promise and Peril

The familiar scrawl of a teacher’s red pen, once the definitive symbol of academic feedback, is steadily being replaced by the silent, instantaneous judgment of an algorithm. From the red-inked margins of yesteryear to the instant feedback of today, the landscape of academic assessment is undergoing a seismic shift. As educators grapple with growing class sizes and the demand for

Legacy Digital Twin vs. Industry 4.0 Digital Twin: A Comparative Analysis

The promise of a perfect digital replica—a tool that could mirror every gear turn and temperature fluctuation of a physical asset—is no longer a distant vision but a bifurcated reality with two distinct evolutionary paths. On one side stands the legacy digital twin, a powerful but often isolated marvel of engineering simulation. On the other is its successor, the Industry