About Us

Better AI

We’ve built an AI detection tool bringing scientific rigor and understandable results to an industry that is currently filled with uncertainty and fear and impacting all of our lives

We believe in Better AI that improves the lives of all humans!

Credit Rosicrucian Egyptian Museum

Our Story

Inspiration Behind The Name Mattie

We are a team of data scientists, physicists, computer scientists, and businesspeople with a common objective to help usher advanced AI into our society, but in a fashion that is balanced, truthful, with justice, and harmonious with human life. In fact, these fundamental principles are represented in our logo, which is an abstract of the ancient Egyptian concept of Ma’at, or as we are calling it ‘Mattie’ (21st century), personified as a goddess. As for our name ‘lanai’, we chose this because of how it embodies the perception of peace and tranquility, whether you are on the beautiful Hawaiian island of Lanai or if you are sitting on a lanai overlooking a lake surrounded by mountains.

Who We Are

We assembled a talented and unique team with over 100 years combined in data science, technology startups, and data science. The hype of generative AI and GPT is relatively new, but members of our team have been researching and developing AI for decades. One of the areas of interest has been how to best identify language that has been generated by a machine versus a human. Much of our interest in this area started back when team members were working on the large language models (LLM) for IBM Watson. Shortly after IBM Watson won Jeopardy! in 2011, it was clear that LLMs were going to quickly achieve even greater heights in both natural language processing (NLP) and natural language understanding (NPU). This motivated members of our team to start researching and building methodologies to better distinguish machine-generated content from human.

In this photo provided by Jeopardy Productions, Inc., Ken Jennings, left, and Brad Rutter, right, pose after the episode of "Jeopardy!" that aired Wednesday, Feb. 16, 2011, when Watson, the IBM-created megabrain, beat the veteran champs with a total of $77, 147 over two exhibition matches.(AP Photo/Jeopardy Productions, Inc.)

Why We Are Different Than Other Tools

Our ongoing research and understanding of how advanced LLMs and machine learning NLP/NLU have evolved led us to the use of common principles and methods used in physics for the last couple of centuries, such as linear regression and concepts around energy and variety (many of us on the team are actual physicists by trade). As humans, we don’t choose our words based on probability (like LLMs), but rather we select words in a much more complex way that is rooted in many facets of what makes us human. For instance, we often choose words based on prior life experiences or emotions. In cognitive science and psychology, this is referred to ad hoc category construction, a way that we categorize objects, concepts, or stimuli in a fluid manner, versus relying on pre-defined concepts or probability of what word should come next, something that a machine simply cannot do now and may never be able to do.

Why Human Text Is Different From AI

Knowing this difference between machines and humans, we developed a proprietary AI detection technology that analyzes the structure of sentences, the variety of vocabulary, and level of energy in the content (how different types of words are used in relation to the entire body of written text). This is exactly why if you ask any AI generative application today to write a poem in the style of Robert Frost or a sonnet in the style of William Shakespeare, the results will be nowhere as emotionally complex, with choices of words much different than the original authors.

We are excited to finally bring this AI detection technology to market and let you use it.

We are hopeful for Better AI!