- AI/ML Clarification


The objective of ML clarification is to help you understand how AI and ML can optimize your business. This clarification will help you determine which parts of your business will benefit the most from AI and ML.

A business analysis will be conducted for each proposed model, which will lead to a business case that will describe the benefits and challenges of implementing each AI / ML model in your business.

In addition, a cost-benefit analysis will be performed for each model, which will provide insight into what dividends a company can get from utilizing AI / ML.

Requirements for AI / ML Clarification

According to the size of the part of a company being analyzed, a ML clarification could be a big project. It is vital that we have access to all the relevant information to ensure that it goes smoothly. If the goal is to forecast fixed expenses, or churn prevention for employees, then for example budgets and bills can be used.

In addition, it is imperative that you take the time to speak with us and spar with us. As you know exactly how your business works, we will definitely need your input in relation to workflows and decision-making processes, so we don't suggest improvements in areas where things are done a certain way for business-specific reasons.

Technical possibilities for an AI / ML clarification

In relation to starting an AI / ML project, a ML clarification will result in a roadmap for the business. This roadmap will provide an overview of which models need to be made and what kind of data you can use to create them. In addition, it will provide an overview of the business benefits you can receive by implementing AI in your business.

In addition, a variety of model types will be explained so you can gain insight into the potential end products you may receive.

There will also be suggestions as to how any models can be most easily implemented in the business, so that employees' everyday lives are as easy as possible.

The process regarding AI / ML clarification

Q-analytics process when we do a feasibility study is:

  • Initial meeting
  • Workshop
  • Data access
  • The analysis phase
  • Result

Initial meeting

In the introductory meeting, we will discuss the scope of the project for clarification, what goals you have in relation to AI / ML projects that will be carried out in the future, and get an overview of the types of data that you have access to.


This workshop is used to determine the type of data you have and its description. The workshop aims to prepare and convey all the information we need to perform clarification. 2-3 hours.

Data access

In this phase, we gain access to the data. We could receive the data and then conduct a preliminary investigation in our office. A preliminary study can also be done locally with you if the data is especially sensitive. Data access and data access methods determine the length of time needed for this. 2-4 hours.

The analysis phase

At this stage, we will clarify and hold regular meetings with stakeholders. As a result, we will be able to create a report that contains all the pertinent information we have gathered through our analysis.


Our final product will be delivered to you, where we will present the results and explain our conclusion. This takes approx. 1-2 hours