aiso-lab: Bolstering Business Progress with Advanced AI

Realizing the necessity of an enterprise that can effectively bridge customer requirements, innovative ideas, and AI’s capabilities, Bienert and Michael Hummel started aiso-lab in Germany

aiso-lab harbors a ground-breaking system that makes this development and deployment of hi-tech AI solutions so seamless for its customer enterprises. With its own data centers and SaaS-based solutions, in addition for clients who demand on-premise solutions without transferring data on public clouds, the company boasts of a high-performance supercomputer that simulates the company’s proprietary neural network framework. The network is based on multiple one-hand and open source platforms for dimensionality reduction, data exploration, and a cognitive workflow to provide easy access to the testing and training data. This enables the customer firm to effortlessly build its neural networks as required on the aiso-lab’s AI environment.

Bienert emphasizes on the subtleties and the un-deterministic characteristics of AI that creates challenges for both global companies and start-ups to deliver AI solutions in the market efficiently. He mentions that AI projects need special skills and agility where bigger companies focusing on numerous verticals miss the mark, while start-ups in the field are mainly founded by data scientists who are inexperienced in understanding customer necessities. Bienert and his team’s domain-specific skills and decades of experience aids in this scenario and the company closely collaborate with its clients at every step of a solution’s development and deployment to eliminate all risks, uncertainties associated with the project.

One such client required a specific translation neural network to translate its vast documents from English to German and vice versa which was not possible using traditional translation software. aiso-lab used the customer’s past translational data to train neural networks on its system and deployed an in-house solution for the client. The customer could internally send documents in one language and instantly get an automated email with the same document formatted in the other language.

The company has an ambitious two-course plan drafted for its upcoming future. As Bienert puts it, “We aim to build customer-centric solutions on more diverse verticals and spin-off separate companies focussing particularly on those, thereby becoming a global outsourcing and project implementation firm for AI services, consultations, and solutions.”