Joerg Bienert, CEO of aiso-lab, outlines the current scenario of European AI market in one sentence. “Though the number of AI-based enterprises in the continent has risen rapidly across multiple industries over the years, most can’t comprehend the prospects, challenges, details, and the exact customer needs of the AI market.” Consequently, realizing the necessity of an enterprise that can effectively “bridge customer requirements, innovative ideas, and AI’s unprecedented capabilities” Bienert and Michael Hummel started aiso-lab in Germany. With extensive domain-experience and business development acumen, they built the company to focus on developing enterprise-grade AI applications according to varied customer necessities and use-cases for the European market, thus assisting in “making European firms ready for AI”.
Bienert informs that aiso-lab follows a four-step strategy to develop any use-case AI solution or application for a client. The process initiates with an educational workshop to detail customers on the benefits of AI in global businesses and society, its revolutionary prospects, and ideas on various use-cases where AI applications might boost business progress for the customers. The company then conducts a comprehensive technical workshop with the customer’s experts on these use-cases to get the client’s business data and evaluate the possibility to build the perfect AI application on these data. Once evaluated, aiso-lab builds a pilot deep learning engine for the customer and tests it rigorously within the client’s operational environment. Upon successful completion of the testing, the AI solution is integrated into the client’s infrastructure and its team is trained by aiso-lab’s professionals to maintain the system periodically.
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.”