Advanced AI engineering
AI offers a fantastic field of opportunities – for young businesses and established enterprises. AI-based business logic creates new business models, expands competitive edge, improves quality, and saves cost.
There are now many tools that facilitate the development of AI applications. However, the actual performance of an AI development environment - time-to-value, flexibility in the development and training of models, cost efficiency, data security, reproducibility, rapid deployment, efficient collaboration, monitoring and maintainability - often only becomes apparent during the course of the project.
During the past years of development of AI capabilities, Ambrosys has been at the European R&D forefront - in major research projects and on industry side. We combine strong AI / ML know-how with profound Cloud/Software development practices. Our our IT engineers work hand-in-hand with users in areas of automotive, energy, and agriculture. The joint goal ist to develop and operate market-ready AI models.
Our teams are well versed with business realities, and when we face new challenges, our learning curve is steep.
We will never, ever, share your contact data with anyone. On our data protection page, you can find out how we ensure that your data is handled respectfully.
See also -> KI Consulting | AI Beratung
ML pipelines, end-to-end, by DevOps standards
Collaborative environments for seamless, convenient and secure workflows
AI solutions from concept to productive app
Data science & data engineering
DevOps training specifically designed for ML engineers
Data lakes and other data solutions, specific to use case
Dedicated packaging and containerization
Automated API generation
Automated deployment
Security solutions
Success stories
Questions and Answers
The short answer would be: Most anyone who wants to tap into the opportunities artificial intelligence offers.
In particular, if
- your business opportunity requires quick scaling
- your ML application is your main source of competitive advantage
- your ML operations need to be seemlessly integrated into your other systems
- you are subject to elevated security or data protection standards
- your application processes large amounts of data
- your data is heterogeneous or from many different sources
- you need to deploy to a variety of different systems
- your trained models shall be optimized or re-trained on a regular basis
we’d think it's worth that we talk about the benefits you gain from of high-grade AI environments and engineering.
There are various ways to make your leap of faith a little easier. E.g. we start with a lightweight consulting project to design the concept - paid by the hour. Then, we complete an MVP at a fixed price. Several shared-risk options are possible in the case of long-term cooperation.
The most effective way we can work for you in the long run are our lifecycle teams. This means: The same dedicated team is responsible for development, deployment, operation, maintenance, scaling up and advancement of your system. This way, communication becomes smooth, motivation high on both sides, and bug fixing easy.
We go out of our way to train our teams in effective DevOps behaviors, as they make complex software systems reliable, adaptable and efficient. Among this set of best practices are continuous integration, continuous deployment, monitoring for rapid detection of deviations, and transparent versioning systems.