Advancing AI for everyone

At Aigoritma, we’re conducting research that advances the state-of-the-art in the field, applying AI to products and to new domains, and developing tools to ensure that everyone can access AI.


Demand and production forecasting in renewables (solar and wind power plants) are extremely crucial for the energy companies. Weather conditions are one of the most important variable for those issues. With our wide range of data sources and in-house technology to reduce resolution, we are able to provide unique solutions.

Use Cases in Energy

Electricity Demand Forecasting

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.

Renewable Energy Sources Production Forecasting

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.


Policies and claims have variable dimensions in the operational, legal and economical perspectives for both the insurance companies and clients. To protect all the stakeholders from overpricing, fraud and loss of time, we have remarkable solutions.

Use Cases in Insurance

Claims Cost Optimization

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.

Fraud Detection

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.

Automated Underwriting

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.

Policy Pricing

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.


Independent of the volume, most of the companies have been witnessing the complexity of stocks, sales predictions and pricing management while the business is expanding. There are smart ways for the management of all the variables with our solutions.

Use Cases in Retail

Sales Prediction

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.

Price Optimization

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.


The quality of production process and equipment’s robustness in every stage has a direct impact on the final product. Artificial Intelligence is helping us to evaluate the data always to keep the production performance on top.

Use Cases in Manufacturing

Quality Control

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.

Predictive Maintenance

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.

See Aigoritma in Action

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