Artificial Intelligence

As a long-standing expert in the field of “Artificial Intelligence”, INVENSITY offers medium-sized companies a cost-conscious and yet tailored offer for the use of AI in system and machine operation as well as in production.

As a company at the interface between engineering & IT, we understand complex physical systems and their data in detail with our >200 employees.

We have the data science know-how to identify suitable machine learning applications and evaluate them together with our customers.

INVENSITY is proud to announce its partnership with AI-specialist Avoncourt.

Avoncourt was founded by Miguel Papic and is a neural networks developer and Artificial Intelligence technology integrator servicing private and public organisations.

INVENSITY is part of the KARLI research project, an AI research project funded by the German Federal Ministry of Economics and Climate Protection with a project volume of approximately €16 million. Together with Continental, Audi, Ford, and Fraunhofer IOSB, among others, we are working on the latest ways to transfer the theoretical potential of AI into practice.

The INVENSITY AI Data Value Report is a practice-oriented consulting offer for the automated analysis of your data.

Within ten days, we analyze your existing (sensor) data and provide you with concrete suggestions for the individual use of Machine Learning.

In addition to the technical feasibility, we also consider the economic added value, for example, through material or energy savings, better system availability, or quality increases.

Our price/performance ratio is attractive for medium-sized businesses because we combine customized consulting with automated data analysis to identify the most economically relevant application areas of Machine Learning.

The automated data analysis checks, on the one hand, the quality of the data (e.g., completeness and consistency) and, on the other hand, the usability of the content using different Machine Learning algorithms. In the process, more than ten approaches are evaluated. The performance of the trained models is compared with each other so that the economic viability of the AI deployment can be seriously assessed.

Digitalization means more than just recording data from the real world. Evaluating it, visualizing it and creating new added value turns data into real value creation. A targeted analysis of existing data, possible value creation and possible technical implementation is necessary to present an optimal data value chain.

Automotive

KARLI Consortium: For intelligent interaction with the vehicle of the future

Defense

NATO Science & Technology Organization: Pathfinding in the terrain using the particle swarm algorithm and mobility maps

Mechanical Engineering

Identify use cases of artificial intelligence for industrial applications with a focus on quick wins and business relevance

Automotive

Technical project management for the calculation and evaluation of KPIs within a machine learning based eye-tracking algorithm

Research Project

Object recognition with NVIDIA Jetson TX2 combined with existing ANN frameworks for benchmarking