DATA & AI engineering

How our AI Engineering supports your digital products

We connect technology, data, and business models into scalable digital ecosystems, creating the foundation for AI solutions that increase efficiency, enable growth, and elevate customer experiences.

We excel at building strong data foundations and modern architectures that unify complex system landscapes, from machine and IoT data to commercial, retail, and unstructured sources.
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In many of our client projects, we design and deploy Datalakehouse architectures that continuously ingest diverse data streams and publish them into the latest AI models. On top of these scalable pipelines, we build advanced machine-learning and predictive solutions that create real business impact, whether it’s forecasting demand, detecting anomalies, optimizing operations, or powering domain-specific products like a high-precision AI skin analyzer. Our strength is connecting data, technology, and products into one coherent ecosystem that makes AI reliable, explainable, and ready to scale.

Our AI Use Cases

AI agent for connected device support

An AI-powered agent provides first-level support for a leading consumer electronics company, helping users with onboarding, troubleshooting, and device setup. It reduces support workload, improves response times, and enhances the overall customer experience.

AI-powered forecasting for smarter fashion planning

An AI-driven forecasting engine predicts Never-Out-of-Stock demand with far higher accuracy than traditional planning models. Powered by historical data processed in a modern Datalakehouse architecture, it helps fashion brands reduce overstock, prevent stockouts, and improve cash flow across their supply chain.

Skin analyzer powering a next-generation beauty platform

A beauty content and marketplace platform uses our AI skin analyzer to capture facial images and evaluate key skin markers. The system provides precise insights on conditions such as acne and wrinkles, enabling personalized product recommendations and a more engaging beauty experience.

From traditional engineering to data-driven service innovation

A global machinery leader expands from hardware delivery to data-driven machine optimization. We built a Datalakehouse that collects millions of datapoints and integrates industrial control into the automation, reducing material and energy use and improving process stability. Predictive algorithms further enhance performance.

AI-enhanced decision-making in raw material trading

A data science solution aggregates, standardizes, and analyzes global trade and market data for a chemical trading company. It uncovers trends and sales opportunities, improves decision-making, and increases operational efficiency.

Our AI Competencies

We integrate AI directly into the digital products and platforms we build: from smart assistants and predictive tools to automated service flows and intelligent user interfaces.

We also use AI internally to accelerate our own processes:
AI-assisted coding, automated testing, intelligent quality assurance. It helps us move faster, stay lean, and build better software.

Data Lakehouse Architecture

Designing and implementing highly scalable, unified data architectures that combine the best of data lakes and warehouses, built for analytics, ML, and real-time insight.

Agentic AI Services

Integrating autonomous AI agents that can reason, act, and coordinate across tasks, unlocking a new level of automation and intelligence.

Machine Learning

Training models to recognize patterns, make predictions, and automate decision-making, the backbone of modern AI.

Deep Learning

Advanced neural networks that unlock complex use cases: from image recognition to generative AI and beyond.

Natural Language Processing (NLP)

Helping machines understand and generate human language: from chat interfaces to intelligent document processing.

Computer Vision

Enabling machines to interpret visual input: for tasks like quality inspection, object recognition, and more.

Recommendation Systems

Delivering personalized user experiences: with collaborative, content-based, or hybrid filtering approaches.

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