AI Strategy and ML Engineering
Artificial Intelligence & Machine Learning
Do you need guidance to reach your destination in the journey into the world of Artificial Intelligence (AI)? We are with you.
Together, we will explore key concepts, starting with the AI strategy that supports your organization in leveraging the transformative power of new technologies.
We will cover the entire field from Machine Learning Engineering to ML Ops, which is the foundation for efficient and scalable implementation of Machine Learning projects.
In doing so, we will learn about the fascinating world of generative AI, for example. This includes Natural Language Processing (NLP), where Large Language Models (LLM) are trained through Machine Learning (ML). You will also learn that pre-processing is crucial in transforming raw data into meaningful information.
Are you ready to open the door to a future with artificial intelligence? We will accompany you on an exciting journey of discovery with the following services around AI and ML:
- AI Strategy and Use Case Management
- Data Science & Pre-Processing
- ML Engineering (Trainingsprocesses, Optimierung, Integration, Testing/QA, UX-Design)
- Computer Vision and Deep Learning
- MLOps (DevOps, (Cloud-)Infrastructure for Machine Learning, Automation)
Our Services in the field of AI and ML Engineering
→ AI STRATEGY AND USE CASE MANAGEMENT
A well-thought-out AI strategy defines clear goals, identifies relevant use cases, and integrates AI seamlessly into the corporate vision. The core of a successful AI strategy is Use Case Management. This involves identifying specific application areas for AI that offer measurable added value to the company. This requires a thorough analysis of existing business processes to identify potential areas where AI algorithms and models can be applied.
Structured Use Case Management enables setting realistic expectations, efficient resource allocation, and maximization of ROI (Return on Investment). This also includes selecting suitable AI technologies like generative AI, with examples like Natural Language Processing (NLP) or areas such as Computer Vision, which are optimally suited to the identified use cases.
→ DATA SCIENCE & PRE-PROCESSING: FOUNDATION FOR DATA-DRIVEN INNOVATION
Data Science and Pre-Processing are the foundations for the success of analyses and insights from large datasets. Data Science, as an interdisciplinary science, combines statistical methods, Machine Learning, and advanced analytics techniques to extract valuable insights from data. The key lies in Pre-Processing, a critical phase where raw data is cleaned, structured, and prepared for analysis.
Pre-Processing involves steps such as removing faulty data, dealing with missing values, and converting data into the required format. Through normalization and standardization, a uniform basis is created. This process is crucial for improving the quality of data and ensuring reliable results in subsequent analysis phases.
→ ML Engineering
ML Engineering is crucial for the development of Machine Learning systems. It includes training processes, optimization, integration, testing/QA, and UX design.
The training process aims to recognize and generalize patterns in data. Optimization continuously improves the accuracy and efficiency of models. Integration requires seamless adaptation to existing systems. Testing/QA ensure reliability and robustness. UX design is important for presenting results in an understandable and effective manner.
ML Engineering requires a comprehensive approach for robust and effective systems.
→ MLOps
MLOps combines Machine Learning with DevOps, integrating best practices and automating the entire ML lifecycle. The use of (Cloud) infrastructures allows for scalable resources. Automation plays a key role, speeding up the development process and improving the deployment of ML models. The agile combination of MLOps, DevOps, and (Cloud) infrastructures optimizes efficiency and reliability throughout the entire ML lifecycle.
→ Computer Vision & Deep Learning
Empower your business with our leading-edge computer vision technology, meticulously crafted to meet your specific needs and drive innovation. From dynamic real-time solutions to customizable and streamlined products, we offer a comprehensive suite of services:
For instance, utilizing state-of-the-art deep learning algorithms for advanced human motion analysis to enhance safety measures in the field of autonomous driving. In the field of supply chain, logistics, and manufacturing we optimize operational workflows through activity recognition and model accurate perception methods for automated quality control.
Beispiel: Generative AI
References in ML Engineering
AI for the Tax Advisory Profession to Explore
The DATEV KI-Werkstatt enables early testing of applications based on generative Artificial Intelligence (AI). It exclusively features early prototypes for AI use cases in the tax advisory, auditing, and legal consulting professions.
Demography-Driven Knowledge Drain
QualityMinds has developed a multi-layered concept that can even strengthen organizations and companies emerging from the upcoming transformation. With the help of Artificial Intelligence, specifically Large Language Models (LLM), it can enable people in companies to secure knowledge and experience.
Ready to take off with us?
YOUR CONTACTS
Tobias Varlemann
Lead R&D
Dr. Namrata Gurung
Data Scientist
Bettina Stühle-Stein
Senior Test Expert
Dr. Michael Mlynarski
CEO
Anything else you need to know?
Let’s talk!
