About Us
We strive to make AI technologies accessible to those within the legal profession. Uniquely combining supervised and unsupervised machine learning, we provide a powerful for the sifting through of a wide variety of medical documentation (handwritten and typed), dually suited for extracting relevant records and completing cumbersome PFSs/PPFs.
The ability to interact with a computer presence like you would a human assistant is becoming increasingly feasible. ― Vint Cerf, a 'father of the internet'
Further, we are avid solution seekers. We maintain there always exists a functioning, relevant neural network suited for any business's unique set of needs and are determined to realize it.
Current status: Available for hire
97% accuracy in the identification and categorisation of documents.
Our models make the most of your data, creating a specialised neural network capable of solving any problem and accomplishing tasks.
Through analysis, our techniques provide your business with valuable perspectives on your historical data.
Our models operate with precision to search through documents for private information and sanitize them, aiding faster discovery.
We train a neural network to read, understand, and retrieve data in order to fill out paperwork.
We base our algorithms on your historical datasets to then apply to new data, forecasting the likelihood of a particular outcome.
We are a team of 3 highly specialized individuals with backgrounds spanning from scientific, academic, and even legal. As a technology-oriented company, we are eager to make partnerships across a multitude of industries. Unlike Google, once you work with us, we do not become your competitor. Our team works hard to ensure that your proprietary data benefits you and only you.
Kappa AI Solutions
We will go over what exactly it is that we can and cannot do. Then we will take a look at your historical data and discuss with you its relevance for our purposes in training your brand new neural network.
Our highly specialised experiences inform our data mining capabilities. In collaboration with your business, we use our own knowledge to extract useful features from your data. Features are attributes or labels, tools to solve problems that we can then apply to our machine learning algorithms. We decide and design features, evaluate their relevance to your business and its needs, test new features, perform quality checks on various models, improve their operation, and go back through the steps of brainstorming and creating more features until a solution for your business needs is found.
Here begins the natural process of building a model. The crucial first step is gathering data. The quality and quantity of the data put in directly determines the quality and quantity of the output. Computer science generally terms this concept 'Garbage In, Garbage Out' (GIGO). After data is gathered, we will sanitize and prepare it for machine learning training purposes. Using our models, we teach the neural network's to perform a task while also training it on the back end to understand how accurately it is performing. Finally, we tune the parameters around the training and refine the model's ability to produce a desired outcome or solution.
Whether your needs center around filling out dense paperwork or perhaps predicting industry and business trends over time -- your freshly built and well-trained predictive, descriptive, or decision model reliably delivers highly accurate and efficient results.
Some people call this artificial intelligence, but the reality is this technology will enhance us. So instead of artificial intelligence, I think we'll augment our intelligence." Ginni Rometty, First woman to lead IBM
By far, the greatest danger of Artificial Intelligence is that people conclude too early that they understand it. Of course this problem is not limited to the field of AI.” Eliezer Yudkowsky, AI Researcher
Our intelligence is what makes us human, and AI is an extension of that quality.” Yann LeCun, NYU Professor
The biggest harm that AI is likely to do to individuals in the short term is job displacement, as the amount of work we can automate with AI is vastly bigger than before." Andrew Ng, Google Brain Cofounder
The best way to predict the future is to invent it... Simple things should be simple, complex things should be possible." Alan Kay, Computer Scientist
There is no reason and no way that a human mind can keep up with an artificial intelligence machine by 2035." Gray Scott, Philosopher of technology
Engineering, Programming, & Product Management
Business Development, Marketing, & Customer Relations
Onboarding, Research, & Writing
