Facing many challenges regarding your quality control, maintenance process and/or yield optimization, you need to discover where to start. Based on your knowledge and our expertise, our team helps you to identify and list your challenges. For each of them together we qualify them with a short description of the potential returns of investment, risks, difficulties, you need to face to be successful with AI. Therefore you get a prioritized list of your projects with our recommendations.
The exploitation of artificial intelligence requires starting from a precise problem/purpose. By bringing together the business expertise of your collaborators and the data mastery of our scientists, a set of business issues to explore can be selected. Based on various criteria such as complexity, feasibility, availability of required data and ROI potential, an evaluation matrix is built to establish an order of priority. This first step is therefore crucial in identifying and evaluating selected ideas. In agreement with the client, this phase will also determine key performance indicators (KPIs) that will be monitored throughout the project.
Wizata's objective is to allow you to take advantage of the benefits of AI very quickly, initially through small, quickly achievable steps that deliver concrete results.
Our specialists will advise you on the stages to follow to build this data record and the appropriate basis for your data analysis projects. Some projects will then simply be postponed.
The exploration takes the form of a practical workshop that lasts on average 3 days and brings around diverse types of key profiles around a table to raise business issues (for example the Plant Manager, the Quality Controller, Head of Operations, etc.). On Wizata’s side, we assemble Data Scientists, Data Engineers and a Project Manager.
We then move on to the "Feasibility Assessment".
The feasibility study covers the first part of the well-known CRISP-DM methodology used for all Data Science projects.
Based on the selected thematic areas, the "FA"’s goal is in-depth understanding of the data itself. From a sample of data, our data scientists will confirm that the data is usable, sufficient and qualitative enough to allow to solve the problem and achieve the estimated ROI.
This essential phase precedes to the key stage of Research and Development, that confirms hypotheses through modelling and powerful algorithms and opens the way to final solutions. The final phase of integration will the start, with an evaluation of the model before its deployment.
Do not hesitate to contact us to ask for more information about these different stages.
Once your have identified one problem to start with, you must study more the business feasibility of the project, its risks and impacts within your production process but also assess if you are ready to start in terms of data amount and quality.
This step, that we call the feasibility assessment, helps you define exactly the resources you need to carry on the project. Therefore you are ready to start building your AI through a research and development process before you can finally harvest its full potential.