Advancing AI for everyone

Unlike the other energy sources, electricity cannot be saved or to be used at another time reliably and cost-efficiently with current technologies. Thus, there should be a consistent prediction for its daily use. Otherwise, electricity distribution companies could incur massive costs.

Energy suppliers are obligated to share their forecasts with the system operator to maintain system balance. Renewable energy production is especially hard to predict because it depends on uncontrollable factors such as weather conditions.

Always the minimum price should be looked out to achieve the cost optimization without reducing the quality standards in claims. The collection of the up-to-date data from the related source according to the subject of the insurance policy and benchmarking the similar cases are helpful to make the required optimizations.

People can claim the cause of loss that is not covered by their insurance or try to obtain some advantage they are not entitled to with the fraudulent actions.

In automated underwriting, the risk perspective of the system and the classification models of the client profiles are so crucial to determine the right assessment and approval path of the related issue. If the model construction of the system doesn’t cover all the issues, there will always be misevaluated cases. Keeping the model always up-to-date is another challenge.

The primary concern of pricing the policies is that one approach does not fit them all with traditional methods while calculating the payout price. Meaning that people with different backgrounds and incomes should be evaluated with different proposed prices.

Forecasting sales is essential for retail companies since it directly affects identifying benchmarks and determining incremental impacts of new initiatives, planning resources in response to expected demand and projecting future budgets.

The traditional market research into sales and customer satisfaction done by companies to optimize their prices can be very slow and may not serve companies’ best interests profit-wise in the long term.

Mass production has an issue with a poor quality because of the human-driven quality control processes. In addition, there is a need to control the quality of products without interrupting (or disrupting) the production process.

The predictive maintenance is related to the equipment’s condition rather than expected life statistics. For this prediction, constant monitoring of the equipment, tracking of anomalies and other equipment operation-related data collection should be carried out to predict the maintenance periods to avoid equipment failure.