Data & AI

Data is the foundation of every successful AI initiative, and we build that foundation. With a clear strategy, reliable data, and AI solutions that help companies make better decisions, faster.

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Our Offerings

The path to productive AI is built on countless data-driven decisions. Which use cases are worth pursuing, which data is missing, which models are the right fit, and how to run everything reliably. That is exactly where we guide you.

Data & AI Strategy

A strong data and AI strategy starts with a simple question: where does the greatest value lie? Together, we identify relevant use cases, assess data, processes, and organisational readiness, and develop a roadmap that fits your business. Governance, the AI Act, and responsible AI are built in from the start.
Data Science

Data rarely answers the right questions on its own. We develop models and analyses that surface patterns and support decision-making. From forecasting and optimisation to machine learning, we build solutions that are grounded in business reality and deliver measurable impact.
Data Engineering

Good decisions require reliable data. We build modern data platforms, establish robust data pipelines, and connect systems into a foundation on which analytics and AI can operate effectively. The focus is on data quality, high-performance pipelines, and an architecture that can carry future requirements as they evolve.
AI Engineering & Operations

We develop AI applications that integrate seamlessly into existing processes and systems. From LLMs and RAG to AI agents, we design the right architecture, connect data sources, and put guardrails and Human in the Loop mechanisms in place for safe, transparent usage. With monitoring, evaluation, and continuous improvement, we ensure AI systems remain reliable over the long term.
Decision Intelligence

Good decisions don't happen by chance. We analyse decision-making processes, connect data, rules, and AI, and make it transparent how decisions are reached. This allows workflows to be improved in targeted ways, accountability to be clearly defined, and business outcomes to be steered with precision.

Our Framework for Effective Execution: PAICE®

For execution, we deploy PAICE®. Our operating system aligns strategic steering, prioritisation, enablement, and delivery into one cohesive approach.

PAICE® creates transparency across the status of initiatives, sharpens accountability, and gives decisions a reliable framework. This is how individual initiatives become consistent, measurable progress.

How PAICE® Makes AI Initiatives Scalable Our Framework for Effective Execution: PAICE®

Measurable Results

Data & AI proves its value in day-to-day business. That's why we measure impact where it happens: in economic metrics, processes, usage, and quality. This reveals what works, where potential lies, and when adjustments are needed.

Embedding Usage in Everyday Operations

Adoption and user satisfaction show whether a solution is embraced in day-to-day work and delivers the expected value in practice.
Driving Business Value

Data and AI solutions improve specific metrics, such as revenue, costs, defect rates, or customer churn.
Higher Productivity, Higher Quality

AI-automated workflows increase speed and enable more thorough quality assurance.
Effectively Supporting Processes

We measure how much of a business process Data & AI covers and how deeply the solution is integrated into operational workflows.

Strong Partnerships

We work technology-agnostic and platform-independent, bringing in strong ecosystem partners where they deliver the greatest value.

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André Bojahr

Director

FAQ

What Is Data Engineering?

Data engineering is a key process in data analytics that focuses on transforming raw data into a structured format. This includes extracting data from various sources, transforming it into a standardized format, cleaning it, and integrating it into a database or data warehouse.

Data engineering is essential for building a solid foundation for data analytics and machine learning. It requires a combination of skills in data modeling, programming, and data architecture.

In today’s world, data plays a central role. This makes data engineering a critical capability for any company that aims to succeed.

What Is Data Science?

Data science refers to the application of scientific methods, statistical models, and programming to large data sets. The goal is to identify patterns, generate insights, and derive actionable recommendations. It includes AI techniques such as machine learning and data mining.

Data science is a key capability for companies to make data driven decisions, understand customer behavior, and unlock valuable insights. Data scientists need strong skills in programming, mathematics, and statistics to create real value from data.

What Is Business Intelligence?

Business intelligence is a process that uses data analysis to support better decision making in organizations. Through data visualization in dashboards, companies can collect and analyze data from various sources such as sales figures, customer feedback, and marketing campaigns in one place.

Business intelligence tools enable users to quickly analyze data and identify trends to make informed decisions. BI helps companies become more effective and gain a competitive advantage by optimizing processes and enabling fact based strategic decisions.

Why Is Artificial Intelligence Used in Data Analytics?

Artificial intelligence is used in data analytics to identify complex patterns and make predictions. Techniques such as machine learning and deep learning make it possible to process large volumes of data efficiently and automate decision making.

By applying AI in data analytics, companies can respond quickly to market changes and generate more accurate forecasts. AI also helps automate processes, saving time and costs. Overall, it enables better data driven decisions and increases competitiveness.

Why Should I Get Advice on Data and AI for My Company?

Consulting in these areas offers several benefits:

Managing complexity: Data and AI are technically complex. Experts help you understand and apply these technologies effectively
Strategy development: We help you build a data driven strategy aligned with your business goals
Process optimization: Identify how AI can make your processes more efficient
Risk reduction: Avoid financial, legal, and reputational risks through expert guidance
Stay up to date: Keep track of the latest developments in AI
Training: Ensure your team has the skills to work with data and AI
Data protection and ethics: Stay compliant and apply AI responsibly
Cost efficiency: Despite initial investments, data and AI can drive long term savings
Competitive advantage: Stand out through effective use of data and AI

Data & AI

Our Offerings

Data & AI Strategy

Data Science

Data Engineering

AI Engineering & Operations

Decision Intelligence

Our Framework for Effective Execution: PAICE®

Measurable Results

Embedding Usage in Everyday Operations

Driving Business Value

Higher Productivity, Higher Quality

Effectively Supporting Processes

Strong Partnerships

FAQ