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March 18, 2025, 1:23 am UTC

Checkfor.ai 93-3260011 | Government Grant Application

Checkfor.ai | Application Preview

 

Checkfor.ai is applying for government grants to enhance its AI text detection software aimed at enterprises and government entities. The funding will be allocated primarily towards operational costs for research and development, focusing on cloud computing for neural network training, and hiring a machine learning researcher to boost innovation.

The company envisions creating a comprehensive authentication solution to tackle AI-generated spam and fraud, with plans to broaden its scope to other formats like audio, images, and videos as technology evolves. With additional funding, Checkfor.ai aims to scale its technology to address the rapidly advancing AI landscape and maintain a competitive edge against increasingly sophisticated threats.

Currently, Checkfor.ai has gained traction by onboarding customers who have submitted over 100 million documents for verification through its solution. The company recognizes the need to expand its trust and safety measures across various online platforms while exploring other security offerings.

A recent technical report showcases the company's state-of-the-art technology in AI detection, positioning Checkfor.ai as a potential leader in next-generation cybersecurity. The rise of large language models (LLMs) has introduced new challenges as malicious actors exploit these technologies for deception. Checkfor.ai argues that an industry-standard protection layer is essential to combat this emerging threat, as existing tools fall short.

In terms of competition, Checkfor.ai faces established players like GPTZero, which is popular among educators for plagiarism detection, Hive AI, and Reality Defender, each addressing different facets of AI content moderation. However, Checkfor.ai's competitive advantage lies in its team's extensive experience in training large-scale deep learning models, which results in a detection capability significantly surpassing its nearest competitor. The company's targeted approach to internet content and its ability to analyze vast amounts of user-generated data further solidify its position as a leader in this space.

  • General Information

    Business Registration Number: 93-3260011

    Location: Brooklyn, NY, United States

    Length of Operation: 1-5

    Number of Employees: 1-10 Employees

    Annual Gross Income: Less than $100k

    Annual Gross Expense: Less than $100k

    Open to Loans: NO

  • Funding Usage

    We would like to use the funding to build out a world-class research team to further our development of the best-in-class AI text detection software for enterprises and government. We will primarily use the funding for (1) covering the operational costs of R&D, which is primarily cloud compute spending to train large neural networks to perform the detection, and (2) hiring a machine learning researcher to accelerate our pace of innovation.

  • Business Plan

    Our long-term product vision is to develop a comprehensive authentication solution to identify and respond to AI-generated spam and fraud tailored to industry use cases and expand to other modalities, such as audio, images and videos. With additional capital, we would be able to massively scale our technology to keep up with increasingly advanced AI and solve the problem long-term. We need to stay ahead on the research front due to the increasing sophistication of adversaries. So far, we’ve started onboarding new customers who have already submitted over 100M documents to be checked by our solution. Through our traction, we believe we can scale and refine our trust & safety business to other online platforms while developing other security solutions. We recently released a technical report [https://checkfor.ai/blog/technical-report-february-2024] demonstrating that our technology is state-of-the-art compared to other AI detection commercial and open source methods, but this is just the tip of the iceberg. We do not view our company as simply AI detection; our business will grow into a next generation cybersecurity company as large language models become widely adopted across industries and across the globe. Just as people have learned to use computing technology for good, bad actors have used computers to manipulate and deceive at scale that had been previously unseen. LLMs are the next frontier: bad actors are already using LLM technology to deceive at even greater scale, causing unprecedented harm. Assuming that AGI is right around the corner, the internet needs an industry-standard protection layer for any form of content generation platform, and current tools are completely unequipped to handle this new category of deception at scale.

  • Self Identified Competition

    GPTZero is a widely used AI detection tool primarily used by educators to check for plagiarism. Hive AI is a content moderation company that provides a suite of AI models and products to enterprises. Reality Defender is another startup that is attempting to solve enterprise deepfake detection, although their primary modalities are audio and video currently. Due to our team’s extensive experience training large deep learning models for industry (Tesla Autopilot, Google Ads), our model to detect AI-generated text is over 9 times better than the next closest competitor (GPTZero). More details on our model’s performance against the competition can be found in our team’s comprehensive technical report. [https://checkfor.ai/blog/technical-report-february-2024] Our team has both the research background and the practical industry experience to reliably train large-scale neural networks. Additionally, our focus on Internet content differentiates us from other AI detection startups that primarily focus on education. Given that there is a wealth of human produced user-generated content on the Internet, we believe that the problem reduces to a matter of who can most effectively develop algorithms that can search and learn patterns in vast amounts of data. We believe that our team’s experience working on similar problems makes us the best-equipped people to solve this problem long-term.

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