Lena Core Engine is a data analysis engine which supported by artificial intelligence (machine learning) algorithms that empower companies to extract information that can be applied to processes from their data. Lena, which is independent of third-party applications, can work on the cloud or offline and supports organizations to conduct their management stakeholders in an efficient way, as well as to improve the process stakeholders (customers, suppliers, project teams etc.).

Lena, which can be integrated into different software processes thanks to its platform-independent structure, is easily fused into the existing processes of the companies and can provide support to autonomous systems by feeding the software. The Lena Core Engine is used in enterprise solutions developed by Intellity AI.


Your Solutions Are Smarter With AI

Special designed and engineered AI alghoritms can produce solid projections and machine learning models.

Through the intelligent models, you can use what-if analysis and you can test your decisions with your data.

With learning models produced by Lena Engine, your solutions and software can be more intelligent. With this way, you can design autonomous software ecosystems.

Interactive & Cross Console Reports

In a rapidly changing environment, business professionals have to reach their tools easily. Our business intelligence tools can be managed with various types of smart devices. It will be good preparing a report or checking company’s current status on the road to office.

IT Management

Today’s rapid shifting customer preferrences’ world puts more value in customer protection. Protecting current customer portfolio is important as much as converting people into the new customers.

In order to handle their customers, efficient customer management algorithms are helping to our succesful partners in their dailiy processes. Algorithm will provide various customer churn scenarios to managers, so they could make proactive moves, before their customer make its leave from the brand.

The inability to predict a surplus or stock shortage causes a lot of questions. When the ordered product is not in stock, the temporal cost caused by the supply of the products will prevent possible gains and lead to customer dissatisfaction. In case of excess stock, unnecessary storage costs arise.

With the predictive analysis, it is ensured that the right product is stocked at the right time and the undesired possible situations are prevented.

  • Decrease in inventory / warehouse costs,
  • Periodic sales increase,
  • Fast and accurate supply of demand and orders,
  • Increasing the efficiency of stock-production planning is ensured.

Long-term relationships can be established with the successful management of a new customer, especially in sectors with high customer circulation, in which the interaction with the customer is intense, such as e-commerce systems.

The learning model to be created as a result of analyzes;

  • Making new product suggestions to the new customer in the system from the first moment,
  • Preparing for the new customer's possible needs or demands,
  • It is aimed to increase customer management efficiency.

In daily tempo, many processes are used in companies. In particular, there are many processes related to human factor in service firms. Failure to direct existing tasks to the right person or unit extends the processes, in return for the company as an additional cost and customer dissatisfaction.

By analyzing the processes;

  • Optimization of existing processes
  • Shortening the Problem-Solution process
  • It is aimed to increase management efficiency.

Shape Shape