We build AI models and apply advanced data science techniques that turn your operational data into a concrete, measurable advantage. Regardless of industry. Regardless of data source.
Forecast before the event happens.
Before orders drop, before a customer churns, before a machine fails. You have time to react, not just a report after the fact. We match the method to the problem: LSTM, Gradient Boosting, survival models.
Patterns hidden in operational data.
Your operational data holds answers your BI does not show. Where you lose margin, what drives sales, which customer segments behave differently. We bring it to the surface.
Unstructured data speaks too.
Reviews, comments, service tickets, documents. Where data is text, there are signals that cannot be processed manually. We turn them into measurable insights.
We work with what you have.
No need to migrate data or build a new stack. We work with what you have: SAP, ERP, Snowflake, your own data warehouse, CSV files. The model fits your environment, not the other way around.
AI platforms and SaaS tools solve general problems. Your problem is specific. Your data is unique. Your patterns are irreplaceable.
A model trained on your data knows patterns no off-the-shelf software can see. It knows when your customers order, how they respond to seasonality, where anomalies arise. A competitor cannot buy that.
SaaS costs more with every year and every user. Your model becomes more accurate with every week of new data. After a year it knows your business better than the best analyst.
We do not ask for a budget before showing a result. We work on your real data, show a concrete number in EUR or USD, and only then do you decide on full deployment.
Generic, not yours
SaaS knows as much about your business as it does about your competitor's. No off-the-shelf tool knows your patterns.
No competitive moat
Anyone who pays for a licence gets exactly the same tool as you. A custom model is IP that nobody can copy.
Ongoing cost with no IP
When you stop paying the subscription, you lose everything. A custom model stays yours and grows in value.
From data audit to production monitoring. We work side by side with your team or independently, if you prefer a ready-to-use solution.
We do not use LLMs where XGBoost is enough. We do not train a neural network where a linear model gives a better result faster. Architecture follows data and the problem, not hype.
Data audit, feature engineering, exploration, training, validation, deployment, drift monitoring, retraining. Every stage with documentation.
SAP, Snowflake, BigQuery, PostgreSQL, flat files, REST API, Kafka. We integrate the model with what you have. No migration to a new stack required.
We deliver production-ready models, technical documentation, and knowledge transfer. Your team can integrate, monitor, and develop them independently. Zero vendor lock-in.
Data audit and assessment
We check quality, completeness, and data potential before starting modelling.
Model design
Algorithm selection, feature engineering, validation and backtest setup.
Deployment and monitoring
Production deployment, automatic retraining, alerts on model drift.
Documentation and knowledge transfer
Full technical documentation and team training on operating and extending the model.
We combine over 30 years of software engineering experience with completed postgraduate studies at MIT Professional Education in Applied AI and Data Science and a Deep Learning Specialist certification at Bitkom Akademie in Germany.
Established ML and data science techniques paired with deep learning, applied specifically to your problem.
We speak the language of business and understand data. Results are measured in EUR and USD, not in model metrics.
We show value before the decision is made. Pilot on real data, a concrete number, then deployment.
An effective AI model requires a thorough understanding of the data, the business problem, and the environment it will operate in.
That is why we start with a data workshop, build a pilot on real data, show value in concrete figures, and only then move to full deployment.
Guido Winger
Co-Founder
Guido Winger combines entrepreneurial experience with deep technical expertise built over more than 30 years in software development, architecture, and strategic leadership.
He worked on data-driven systems and analytical approaches close to data science and AI from an early stage. Today he helps companies translate technological potential into viable strategies, realistic roadmaps, and productive AI solutions with measurable business impact.
Mariusz Pianowski
Co-Founder
Mariusz Pianowski shapes the strategic and technological direction of the company, bringing over 20 years of experience in developing, modernising, and scaling complex software systems.
He analyses internal processes, identifies optimisation potential, and translates findings into sustainable strategies for greater efficiency and scalability. His focus is on the hands-on integration of AI into existing architectures with a clear commitment to quality, scalability, and responsible implementation.
26 % der deutschen Unternehmen nutzen KI – EU AI Act ab August 2026. 23 Seiten Marktdaten, Handlungsempfehlungen und Prognosen für den Mittelstand.
Kein Spam. Jederzeit abmeldbar. Datenspeicherung nach DSGVO.
Want to use AI in your business? Let's start the conversation. Share a few details and we will respond within one business day.
Location
Hamburg