Implementation

• Data analysis

For successful implementation of RPA and AI, it is important to have access to sufficient and good quality data. The data must be properly prepared and cleansed of irrelevant or erroneous values.

•  Choosing a solution

There is a wide range of AI solutions available on the market, varying in capabilities, features and pricing. When selecting RPA and AI solutions, it is important to consider the specific needs and requirements of the business.

• Solution implementation

Implementing an RPA and AI solution can be a challenging process that requires collaboration between different departments of a company. It is important to have a clear implementation strategy and to implement it in a phased manner.

• Testing and deployment

To implement solutions, it is important to test them thoroughly to identify any bugs or flaws. After successful testing, the solution can be deployed into live operation.

• Monitoring, improvement and maintenance
  Once the solution is deployed, it is important to monitor and maintain it regularly. It is necessary to monitor its performance and make adjustments and updates where necessary to improve the solution.

Benefits

• increase efficiency and productivity,
• improving customer service,
• developing new products or services,
• automating routine tasks.