Take advantage of the potential of artificial intelligence!
The project process
Our goal is to deliver software with the highest quality standard in the shortest possible time. Based on our many years of experience, we have therefore developed an agile, benefit-oriented project process.
Together with you, we develop potential applications for AI in your company. A solution scenario is then defined.
2. data analysis
An AI project only makes sense if the data quality is sufficient. Therefore, your existing data will be analyzed to determine if the project is feasible. If the data is insufficient, an alternative solution is sought.
3. proof of concept
If the quality of your existing database is sufficient, an AI solution model will be implemented. The end result is a POC (proof of concept) that you test.
Based on the test results, final optimizations are made. After your approval, the MVP (Minimum Viable Product) goes live. Subsequently, other projects are possible. We are also happy to support you within the framework of a support contract.
References and projects
We are pride of ourselves on moving our customers forward. That is why we would like to introduce you to some AI solutions that we have successfully implemented together with our customers.
AI solution for the scan up. AG
Artificial intelligence is omnipresent – and is now also conquering the field of human resources. Especially in the field of aptitude diagnostics, the support by machine learning opens up promising possibilities. Based on expert judgments, AI models can be trained to identify suitable candidates. HR experts can thus be relieved, whereupon a targeted focus on selected cases and targeted consulting services can be provided.
WOGRA has been commissioned by the Berlin Scan up. AG developed such an AI model for ranking candidate responses in the Operant Motive Test (OMT). In addition, a possibility of playful interaction with the model was created for the experts. The result is impressive: The AI delivers the correct classification of candidates in over 90% of cases. The Scan OMT AI solution was implemented using the Scikit-learn and TensorFlow AI frameworks. Angular and TypeScript were used for optimal presentation in the frontend. Two AI experts from the WOGRA team worked on this project over a total period of six months.