James Factotum is an intelligent tool that allows you to use Artificial Intelligence to obtain information and data more simply and intuitively.
James Factotum connects to the Business Intelligence software and allows for natural language interaction thanks to the identification of meta tags in the dataset.
James Factotum is based on the conception that the added value given by the end user is about data interpretation rather than the creation of reports using complex User Interfaces (UIs).
Furthermore, James Factotum comes with an advanced neural network that allows it to make previsions that are more accurate than the ones made by the Business Intelligence Software using traditional statistical tools. It is possible to use these forecasts in two ways:
1. Asking them directly to James: “How big will the EBITDA for the current quarter be?”
2. Using a proactivity function, that allows James to autonomously conduct simulations on data and identify potential opportunities and risks: “If the AF320 Project is not completed by the end of next week the chances of not reaching the quarterly EBITDA goal will increase by 58%. I suggest that you ad two resources to the project, enhancing the development area.”
What it does
Understand natural language to interact with the company’s data
James Factotum is capable of understanding natural language and convert it into an input to communicate with the Business Intelligence software. The use of natural language as a mean of interaction removes the learning curve barrier, thus saving significant amounts of time and having the user focus only on the activities that create value.
Creation of forecasts about future scenarios using “White Box” Neural Networks and causal correlation.
James Factotum can create future scenario analyses thanks to the AI networks developed by Divisible Global, more potent than the traditional prevision systems used by Business Intelligence software.
Divisible’s causal correlation algorithm is capable of identifying cause-effect relations within data (and not only mathematical ones, as happens with statistical correlation), while the White Box neural network provides a detailed overview of the most relevant variables that affect the end result.
Using proactivity to autonomously produce scenario simulations to identify potential opportunities and risks.
James Factotum can autonomously simulate scenarios to immediately identify opportunities and risks that may happen thanks to its Proactivity function, all with settable custom goals that can act as guidelines for James’ analyses on the goodness of scenarios. For example, if we want to increase sales by 12% by the next year, James can tell us that marketing expenditures are not a good investment, giving us an optimized scenario.
Supervised and Unsupervised Learning
James Factotum can learn to improve its predictive model as time passes, by comparing old forecasted data and actual data (supervised learning) and analyzing new data (unsupervised learning).
Customization of models through Hornet AI.
James Factotum is capable of developing predictive models that answer to the primary needs of a company and is the result of years of field studies and experiences. But, since we know that every firm has different needs and preferences, we developed an integration with our Hornet AI technology for James Factotum that allows for the independent creation of machine learning models to answer to all the question that a company may have.
Data Storytelling: Optimized report creation
James Factotum can help the user in transforming the multitude of data into useful information to take effective decisions – one of the hardest challenges nowadays. James Factotum can recognize data types and guide the user in the creation of relevant and trustworthy reports.