Advanced analytics and machine learning

From data to competitive advantage

Data science and machine learning methods can identify complex, previously unknown patterns even in a large volume of data. This enables predictions to be made allowing:

Optimisation of complex business process
Automated decision-making

This generates a significant competitive advantage. We can help you develop a viable solution with our technological and methodological experience around artificial intelligence and machine learning methods: right from Proof of Concept (PoC) to a productive and scalable solution.

Frequently asked questions on the way from PoC to marketable solution

What are my ideas and goals? What is it I want to know, find out or be able to predict? (Automatic detection of defects, for example).
Is the data suitable for solving the problem or answering my question?
Are algorithms suitable for solving the problem?
After an initial analysis of the technical framework (cloud or local): Is it possible to implement my idea in this way? (Example: I have images of defective plant and want to check whether machine learning methods can be used for automatic defect detection).
Which other potential use cases can I implement with the data?

At a glance: Added value through the use of advanced analytics and machine learning methods

The challenges of machine learning as a value-added technology – examples from the manufacturing and automotive sectors:

Predictive maintenance in practice

The research division of a plant manufacturer has developed a machine learning model to predict the energy output and service life of wind turbines. The company now faces the challenge of releasing this model to the market as quickly as possible, as a productive solution that can also be used to efficiently analyse large volumes of data from several thousand turbines.

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Achieve your goal with doubleSlash: Successful implementation of your advanced analytics project

As a consulting and software company, we cover the entire range of services from data science strategy and integration right through to data analysis and data visualisation. And we’re also pretty good at data engineering. Thanks to our many years of experience in designing and implementing complex IT projects, we’re the perfect partner to lead your advanced analytics project and machine learning to success. Here’s what we can offer you:

Our services:

Checking of existing AI solutions or PoCs
Evaluation of suitable technologies such as Python libraries, cloud environments (AWS, Azure)
Use of standard frameworks (BERT, for example)
Use case implementation with Python, Tensorflow or Matlab
Structured analysis of data quality regarding text or image recognition
Economic feasibility study (ROI calculation)
Product support (market analyses, business model consulting)

Results and artefacts:

PoC: lean testing of market feasibility
Basis for evaluating the potential of your data and feasibility of your use cases
Comprehensive decision template to drive the project forward within the company
Recommendation of the appropriate technologies and methodologies stack
Learn and apply: benefiting from the experience of methodology and technology experts
Automated business processes to facilitate forecasting and automated data-driven decisions

What we bring to the table:

We are familiar with all the relevant machine learning methods (especially NLP, computer vision, predictive maintenance) and will help you select and use suitable advanced analytics technologies.
From the DIY workshop to productive operation: We have solid experience implementing software projects and are not afraid of large, unstructured and fast-moving data (Big Data).
Our highly trained data science experts use their in-depth mathematical and statistical know-how to determine which algorithms and methods are best suited to your specific advanced analytics use case - and implement them accordingly.