Proof of Concept and AI project.

Do you need a solution for an individual challenge?

State-of-the-art research and technology

Honest feasibility assessment

Tangible and tangible results

Transition to operation and rollout

AI projects and POCs (Proofs of Concept).

The project and the proof of concept provide security and predictability. Together, we examine a business objective for its feasibility and demonstrate that this goal can be achieved in an economically and qualitatively satisfactory manner.  

+ Feasibility Assessment   – Input for Business Case
+ Practical Proof  – Testing and Demonstration Environment
+ Risk Mitigation   – Defined Scope with Fixed Time and Effort
+ GAP Analysis   – Evaluation of Necessary Next Steps for Operation & Rollout

Honest feedback & tangible results.

There is a lot of fake news and myths surrounding AI and generative AI.
Some consider this technology to be the solution to all problems.
Others believe that AI can’t solve your challenges.
There is no one-size-fits-all answer to this question.

We have made it our mission to create solutions that deliver real value and solve problems on an equal footing with medium-sized companies and corporations.
We think long-term, economically, and have a strong connection to HSBI (Bielefeld University of Applied Sciences) and research as a university partner.

Let’s talk about your challenges and find out if a POC can provide an answer.
Warning: If a POC doesn’t make sense, we won’t recommend it.

Process of the POC for your AI project

The project for the proof of concept has a fixed duration and is divided into four phases.

01

Business Understanding

Understand business needs, understand business case, capture requirements.

02

Data Understanding

Receive, view and evaluate data.

03

Data Preparation

Generate data, extract and edit data.

04

Usable POC

Training & research, generating evaluation results, testing, obtaining feedback.

Data science and digital consulting for AI projects.

Prof. Dr. Frederik Bäumer |  
Tech Lead Data Science

Professor of Business Informatics,   with a focus on Data Science.  

Dr. Sergej Schultenkämper | Data Scientist 

Dr. rer. nat., specializing in Business Informatics. Data Science

Prof. Dr.-Ing. Hans Brandt-Pook | Consultant

Professor of Business Informatics with a focus on E-commerce and web applications 

AI pilot project – Steps to Go 

The investment in a POC for your AI project is clearly outlined – with defined work packages, duration and effort.

Business Understanding

Together with you, we understood and recorded the goals and requirements of your use case in the workshop.

Data Preparation

We have processed the existing data and, if necessary, generated and obtained new training data so that we can train and prompt.

Data Understanding

We have reviewed and understood your current data in terms of characteristics, format and inconsistencies as well as gaps.

Usable POC

It is important to us to deliver a tangible result directly in the proof-of-concept and to achieve a technical breakthrough that you can use and test.

Project Management

We regularly exchange information on milestones, conduct workshops and generate a presentable result.

Any questions?

Time for a personal conversation.

We aim to assist companies in leveraging data and current technology to solve business-critical challenges. This requires open exchange and transparent communication on an equal footing. I am more than happy to help with this.

You don’t need an individual solution…

 How do you handle access to ChatGPT and translations?