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

Sui vs. Ethereum: A Comparison of Scaling and Architecture

The Move programming language used by Sui treats digital assets as resources to eliminate reentrancy bugs at the compiler level rather than through manual audits. This fundamental innovation has established a new benchmark for smart contract safety at a time when the decentralized economy is processing trillions in annual volume. In the current landscape, the industry is witnessing a sophisticated

Can macOS Successfully Run on Snapdragon Windows Laptops?

The Snapintosh project serves as a technical blueprint for running high-end Apple software on a diverse range of Qualcomm-powered devices and portable devices. This initiative marks a definitive moment in the computing landscape as enthusiasts successfully navigate the transition from Intel-based systems to the highly efficient ARM architecture. The convergence of hardware standards in 2026 has allowed for a renewed

Vertice Launches AI-Driven Procure-to-Pay Platform

Strategic spend management requires more than passive record-keeping, moving instead toward agentic AI that identifies and corrects financial discrepancies automatically. Vertice has successfully transitioned from a specialized procurement utility into a robust, end-to-end financial ecosystem through the launch of its integrated Procure-to-Pay platform. This development represents a significant milestone for the company, which previously focused on the Intake-to-Procure segment of

Anthropic Launches Claude Duet Proactive AI Agent for Work

As a dedicated productivity tool, Claude Duet focuses primarily on professional and operational workflows rather than the casual personal errands handled by traditional voice assistants. This shift represents a fundamental change in how software interacts with the human workforce, moving away from the static request-response cycle that defined the early era of generative intelligence. By operating on a persistent cloud-based

Closing the Privilege Gap With Idira Integrated Governance

The mover phase of an employee lifecycle often becomes a security black hole where old permissions are retained while new ones are added to the profile. This specific phenomenon, frequently referred to as privilege creep, creates a widening gap between the access an individual actually requires and the expansive permissions they technically possess. In the current cybersecurity environment of 2026,