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Our expertise > Predictive AI

Navigate the future insightfully with predictive AI

At the heart of our approach is a deep understanding of your unique challenges. We begin by thoroughly analyzing your problem and then determine the most effective AI-driven solution. Among our diverse toolkits is machine learning, a powerful asset for predictive analysis. Let's delve into how it functions and explore its potential to drive value for your company.
What are the scientific foundations behind predictive AI?
Predictive AI thrives on the challenge of forecasting the unknown based on known data.
Most problems requiring this family of approaches will fall within these key categories:
Regression
Problems of this class involve predicting a continuous quantity from known information. For example, forecasting tomorrow's temperature based on historical weather patterns.
Classification
Here, the goal is to categorize an observation into distinct classes based on past information. A common example is predicting whether a patient has a critical disease.
Anomaly detection
This involves identifying points in a dataset that deviate from the norm. For instance, detecting unusual credit card usage to prevent fraud.
Clustering
This class of methods group similar observations together to manage them as subgroups. An example is categorizing students based on academic performance to better recommend extracurricular activities like mentorship programs or competitions.
At IVADO Labs, we master the art of building a solution tailored to your specific needs.
The scope of scientific methods available to tackle these problems is vast, ranging from tree-based models like random forests and gradient-boosted trees to neural networks, support vector machines, nearest-neighbor approaches, and auto-regressive models to name a few. We carefully categorize the problem, assess the available data, and select the most suitable approaches to optimally leverage this data and provide you with the best business value.
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How can predictive AI
serve your business
objectives?
Predictive AI has become an integral tool across various industries, offering scalable solutions to key business questions, whether it's forecasting product sales, predicting customer behaviour, or estimating when equipment should be maintained.
Consider these examples of critical questions that can be addressed effectively with predictive AI:
Sales forecasting
"How many units of this product will we sell next week?"
Demand prediction
"What will be the number of new seat bookings before a specific flight departure date?"
Inventory management
"How many spare parts will be required in the upcoming month?"
Customer behaviour analysis
"Which customers are likely to upgrade their hotel room?"
User engagement prediction
"Will a customer on a retail website interact with a sales agent?"
Predictive maintenance
"Is it time to plan maintenance for a specific aircraft part?"
Data at the core of predictive AI approaches
To leverage predictive AI approaches to solve these problems or any other similar problems, data is always required. Whether it is past sales transactions, past booking history, aircraft part sensor data, GPS trajectories, medical videos or images, text descriptions of shipments, we will help you to identify which data is required, recommend data to start collecting if relevant and work with you to extract the maximum business value of what is available.

We turn this expertise into added value for your business.

Discover how AI can help you tackle your challenges

Our promise: proven cutting-edge artificial intelligence solutions to solve your most complex problems.

Learn more about our process
Contact us to see how you can put AI to work for your ambitions.