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Perhaps the most powerful ability of AI is where the system predicts a current outcome based on variable learnt past events.
Being able to automatically predict or forecast what is most likely to happen based on past events is an extremely powerful tool in all aspects of business and industry operations.
By learning from past experience, including positive events, negative events, and all the in-between highly variable outlying and unpredictable events that happened before; future decisions are more insightful, more meaningful, more accurate, and more likely to result in a beneficial output: e.g. financial gain, increased efficiency, lower risk, improved processes, better customer journey mapping and experience, or greater consumer satisfaction.
Crucially, a faster, accurate decision potentially saves time, cost and other resources in the future.
The more past data, experience and events to learn from the more insightful and informed we can make our predictions and decisions.
Learning from past events to make a new predictions might sound straightforward - it is of course exactly what a human brain does - but making this process automatic and asking a machine to do this is extremely complex and demanding, simply due to the huge amount of variation involved.
If a traditional software programming approach was used, the computer would continually be asking "if this, then do that; if x and y, do z". This stepwise methodology is extremely limited and tedious as the program will only do what it has explicitly been told to look for by the programmer; making it next to impossible to account for all possibilities and variations, even in the simplest of tasks and events. You certainly couldn't use this approach for complex and diverse scenarios.
With AI and Machine Learning technology it is now possible to learn from huge amounts of variable, constantly changing data and past events in order to make much more accurate decisions, automatically.
ELDR Predictor is Fennaio's core AI predictive analytics software. Using our powerful ELDR AI Engine, which is a Deep Learning Artificial Neural Network, the software uses both Supervised and Unsupervised learning to make and link all the relationships from data (of any size or complexity) passed to it.
When ELDR has learnt (trained) from the data, it is then primed to receive current-status data from which to make a prediction from.
Consider you are a Financial Company and over the last 2 years you have given loans out to 100,000 customers, however you have noticed a variable degree of success, and would now like to make much better informed lending decisions. You have about 50 data points including e.g. "Age", "Postcode, "Credit Score", "Gender", "Education Level", "Credit Score", "Job Title", "Marital Status"....."Customer Status".
With ELDR Predictor, you simply pass the entire data set in, it will self-sort and label the data, self-optimise, self-learn and using a combination of Supervised and Unsupervised Learning will make all the links between all data sets, accounting for wide variation; in this example of 30 data sets with 100,000 rows of data there are ~ (30 x 30 x 100,000) 90 million possible combinations. You can then probe ELDR for a prediction by sending in a single current data set (or this case a loan application).
ELDR Predictor can handle and learn from multiple sources, sizes and complexities of data for numerous prediction requirements simultaneously. Data can be changed at any time and it can continually learn. The software can carry out supervised and unsupervised learning.
By default ELDR is plug and play - you can simply give it appropriately formatted data and it will automatically learn from it, including self optimisation and self scaling.
In many cases you may be happy with plug and play, however almost everything in ELDR is configurable; from which data fields to use as inputs and outputs, to colours, displays, output format, learning modes, learning accuracy, all the way through to Artificial Neural Network dynamics and dimensions.
ELDR Predictor uses a rich intuitive GUI Dashboard from which to manage the whole AI process (data preparation, learning, outputting and testing), including a comprehensive suite of gamified charts and other visual displays to monitor everything.
AI Integration is our speciality. We understand that AI can be used in a variety of ways and in numerous system-types and processes. We build our software to be entirely modular and there are multiple integration methods and points ranging from network-based RESTFulAPI integration to direct coupling at the code level, depending on the response time required, amongst other considerations.
As well as Predictive Analytics software for the Science and Research industry, we provide a comprehensive set of other Artificial Intelligence, Machine Learning, Deep Learning and Data Science software:
Whether you are starting out on your first AI project, just interested in the possibilities of AI or are wanting to expand your existing AI suite, we are here to help.
We will discuss with you where you are, where you want to be, and how we can achieve it with AI - whether by a bespoke solution or using one of our off-the-shelf products
We will work with you to gather, analyse and prepare all your relevant data sources for use in the AI system(s)
We will run and tune the AI throughout the AI learning process and enable the AI to produce a real time visual output to confirm the AI is producing beneficial results
When you are satisfied the AI is delivering the results you desire, we will integrate the AI with your new or existing systems
Fennaio has the expertise in the Science and Research sector to get you up and running with Predictive Analytics AI and Machine Learning in your new or existing systems, software and operations.Get Started