AI Embargo

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The Problem

Data leaks, particularly via email, pose a significant threat to companies, leading to financial loss, reputational damage, and potential legal repercussions. Traditional methods like NDAs and basic data encryption fail to identify the source of leaks, leaving companies vulnerable. In a world where digital communication is ubiquitous, there’s an urgent need for advanced, proactive solutions to detect and prevent these leaks before they cause irreparable harm.

The solution

Even with 1-10% of the words changed, small shifts in grammar, combining sentences, or using synonyms can create thousands of variations. Storing these versions is a solved problem. And brute forcing to find the exact match of a pasted paragraph with one recorded can be optimized further. At the crux of the this project is (1) Use multivariate testing and large language models (LLMs) to create unique variations of every page of the document that is to be shared. Making it possible to compare a paragraph leaked with the exact source of a leak. By tracking specific patterns and document changes, this method can pinpoint which recepient/employee leaked confidential data. This innovative approach strengthens security, offering an unprecedented method for data loss prevention. Getting Gemini API Key will be required, and is out of scope of this project. Cloning and setting up project in a self hosted on premise environment is doable, but a guide to do so - is out of scope of the project/documentation. Although this pilot starts with textual content from documents or emails, in the future it eventually can expand to all forms of sensitive enterprise information, from images, video frames or even LLM weights.

Why Now

With over 1,800 data breaches in the U.S. in 2022 alone, and rising regulatory pressures from GDPR, HIPAA, and CCPA, companies must prioritize information security. The data protection market is projected to reach $65 billion by 2028, showing rapid growth. This urgent need, coupled with advances in AI technology, makes it the perfect time to leverage AI-driven solutions to tackle the ever-growing challenge of data security.

The Market

The global enterprise data protection SaaS market was valued at $7.9 billion in 2023, expected to grow to $20.1 billion by 2028. Data Loss Prevention (DLP) solutions are set to grow at a 21% CAGR through 2028, while Information Rights Management (IRM) solutions will reach $1.1 billion. Our AI-driven approach, addressing document and data leaks, positions us to capture a significant share of this expanding market, meeting the needs of companies striving to remain compliant and secure.

Built With

• gemini
• natural-language-processing
• react