BETTER DECISIONS START WITH THE RIGHT FORECASTING.

As forecasting architects, we combine methodological excellence, planning reality, and system-open implementation. The result: forecasts that are not only statistically sound, but enable better supply-chain and S&OP decisions.

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Google Cloud reports on AlphaEvolve at BASF in collaboration with prognostica

The article focuses on a data-driven digital twin for complex supply-chain decisions at BASF Agricultural Solutions, developed in collaboration with Google Cloud and prognostica.

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Tailored forecasting solution

+20% better planning figures | -40% effort

Enterprise SAP planning enhancement

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Forecasting sparring

+10% forecast accuracy

Hierarchical demand forecasting at Blum

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With us, forecasting in S&OP becomes truly effective.

Many companies have tools, planning teams, data-science expertise, and ERP systems. Yet important questions remain unresolved precisely at the critical transitions between forecast, planning, and decision-making.

We bridge the gap.

Because forecasting only works when three worlds come together.

Questions companies bring to us

How can we improve our forecasts further?

Which planning level makes sense?

Which special effects belong in the forecast?

Which forecast deviations are relevant for decisions?

Which external drivers could improve the forecast?

Which cases need special logic instead of a standard forecast?

What if certain situations occur?

How do we generate better forecasts or planning proposals for a specific case?

How can we improve our forecasts further?

Which planning level makes sense?

Which special effects belong in the forecast?

Which forecast deviations are relevant for decisions?

Which external drivers could improve the forecast?

Which cases need special logic instead of a standard forecast?

What if certain situations occur?

How do we generate better forecasts or planning proposals for a specific case?

We bring together

Forecasting excellence

Understanding models

High-end forecasting expertise for critical planning decisions. For more than 12 years, we have worked on forecasting questions where standard methods are no longer enough. And because our forecasting expertise has been built into the software future, we bring not only sound judgment to projects, but also a real accelerator.

Supply-chain expertise

Understanding planning

We know the language and the requirements of the supply chain. Inventory, service levels, lead times, demand reviews, and S&OP are part of our daily work. This is exactly where we translate forecasts into practical, usable planning logic. That is how a forecast becomes a reliable lever for real decisions. Many successful projects, awards, and patents support this approach.

System-open implementation

Mastering systems

We consistently think from the perspective of your existing system landscape. We shape SAP IBP, OMP, ERP environments, prototypes, interfaces, and workflows so they fit smoothly into existing solutions. Whether it is a dedicated prototype interface, highly specific workflows, or a solution that should later be migrated, we know how to implement sovereign AI in a technically robust way so that it remains adaptable, interface-open, and as platform-independent as possible.

Three perspectives. One forecasting architecture.

Some questions can be clarified in just a few minutes. Others require a prototype with real data. Others become a lasting agent workflow. We step in where the greatest leverage for your supply chain lies.

Forecasting Architecture

From the forecasting question to better decisions.

Companies usually come to us in three situations. You may recognize yourself in one of them:

As forecasting architects, we help identify the right lever, develop specialized planning logic, and bring forecasting intelligence into operational decision-making processes.

Understand -> Improve -> Decide

1. Enablement

You need that crucial impulse

Strategic forecasting sparring

forecast accuracy measurement indicators methods grouping

When it is still unclear whether data, methodology, KPIs, processes, or system limits are the real issue. We help identify the most effective lever with precision.

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2. Specialization

You need a specialized solution

Supplemental planning logic

cold start performance tracking events and promotions

When your ERP or standard system does not model your planning reality precisely enough. We develop tailored forecasting and decision logic for cold start, intermittent demand, events, inventory, and other special planning requirements.

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3. Decision Support

You need better decisions in the process

AI agents for demand review & S&OP

manual reviews unclear priorities missing follow-up

When deviations, priorities, and actions are still identified, discussed, and documented manually. We support preparation, explanation, and follow-up so that forecasts lead to reliable decisions faster.

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What our customers and partners say

“We already observe a substantial improvement in our planning and are able to check off the initial targets. This state-of-the-art technology makes our lives easier.”

Bosch Rexroth AG

“Deriving forecasts from a small data history, as in our case, requires appropriate methodology and techniques. In prognostica, we found a partner who was able to address the special requirements of forecasting sales for fast-moving consumer goods. Our gateway to AI!”

“There are many companies that claim to be experts in machine learning because it is currently trending, but prognostica truly masters it. With a partner like this, it’s possible to implement outstanding solutions, especially in the field of computer vision.” – Robert Schachner, CTO.

“The collaboration was very good, professional, and at the same time very pleasant. Together, the best solutions were found, and the project was successfully brought to completion. We look forward to the next joint project with prognostica.”

“Your approach identifies aspects that we had never previously considered so critically. Through your methodology, I am sure we will experience many more ‘aha moments,’ and I look forward to further collaboration.” – Peter Jetzer.

“With prognostica, we had a competent partner, especially appreciating their pragmatic approach. Together we were always able to quickly respond to new requirements and find solutions. Ultimately, we achieved more than we initially thought possible.”

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Events

Meet us at in-person events or online.

Webinar – AI Agents in Supply Chain Management: The Big Picture

Jul 15, 2026, 12:00 – 12:45

Online

AI agents in SCM explained in plain language: from bots to agents, from skills to governance, with the demand review agent as a practical example.

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FAQ

What does prognostica stand for?

prognostica stands for tailor-made data science and AI solutions that help companies make data-driven decisions. Our name represents our mission: to develop precise forecasts and innovative AI applications that are perfectly aligned with our customers’ requirements.

Which services and products does prognostica offer?

We offer cross-industry solutions in the fields of data science and artificial intelligence. Our main focus is forecasting (predictive analytics). Our consulting services are frequently requested in the areas of demand & sales forecasting, IoT data analysis and predictive maintenance, computer vision, remote sensing and generative AI (possible use cases). However, the possibilities are not limited to these applications: Our data scientists have exceptional expertise in data analysis, forecasting, programming, and cloud solutions, which allows us to implement highly individual AI-based solutions together with our customers (our services). We also offer a standardized forecasting software called future. More information is available on the future website.

How does collaboration with prognostica work, and why is an agile and exploratory approach so important to your team?

In innovative data science projects, especially in the early stages, it is often impossible to define the exact approach, the full potential of the data, or all needs and requirements in detail upfront. These often only emerge during the process. Therefore, we embark on a journey of discovery together with our customers, working in short, rapid development cycles and reacting flexibly to new insights. For collaboration with our customers, this means:

We immerse ourselves deeply in our customer’s challenge and engage in close dialogue, sharpening the understanding of what is possible on both sides. Together, we define how the data can deliver the greatest value.
We create early, often prototypical results (a “minimal viable solution”). Our customers’ feedback is especially important at this stage, allowing us to adjust course where needed.
We stay flexible, experimenting with various – even unconventional – solution approaches. Based on insights and customer feedback, we iteratively refine and expand the solution.
Regular alignment and transparency are essential. We share interim results early on and respond flexibly to customer needs.

This is how we ensure that the solution we develop as part of our consulting fits our customers’ needs precisely, that we work efficiently by focusing on what matters most, and that we avoid heading in the wrong direction. In this way, we can fully unlock the potential of the data and develop the best possible data-driven solution for the challenge at hand, one that fits both the customer and the specific system landscape of the company.

How are data protection and confidentiality ensured in the collaboration?

Data protection, data security, and confidentiality have top priority for us right from the start in working with our customers. As a rule, we conclude non-disclosure agreements with our customers before we see or receive their data or learn any project details. We follow the need-to-know principle: Only those team members working on the respective project are granted access to customer data and systems (e.g., GitLab projects or cluster access) that is necessary to perform their tasks. Additional information on the handling of personal data can be found in our privacy notice.

Which industries benefit from prognostica’s solutions?

Our solutions are used across a wide range of industries – essentially wherever there is data. For example: manufacturing, mechanical engineering, retail, chemicals, automotive, agriculture, and consumer goods. In every collaboration, our customer contributes the specific industry and company knowledge, and we contribute the data science and AI expertise. Through this synergy and close cooperation, we ensure that industry-specific challenges are addressed and solved as effectively as possible using data-driven methods.

Where is artificial intelligence (AI) in prognostica’s forecasts?

Where do we begin? It starts with the fact that, in addition to statistical forecasting methods, we also use machine-learning approaches. It continues with the use of foundation models for time series – something like large language models (LLMs), but for time series instead of language. We also use LLMs, for example, to search the internet and identify factors that may be relevant for forecasting. In addition, we build AI assistants that can help interpret forecasting results and generate reports. Using AI, we derive time series from satellite data that describe crop growth in order to generate forecasts in the agricultural sector. That is just a small excerpt of how AI is used in our forecasting. Should we keep going?

What are large language models (LLMs) and how does prognostica use them?

Large language models are AI models that can understand and generate natural language. We use them in chatbots and for text analysis, for example, to improve our customers’ support and sales processes and increase their productivity. They are also useful for knowledge management within the company. One of our particular strengths is linking LLMs with forecasting, so that forecasting results become even more understandable, more accessible, and more usable. Because we see ourselves as a technology-open AI consultancy and therefore work across technologies, we can run large language models both on major platforms such as Microsoft Azure or Google, and locally with open-source models.

How does prognostica differ from other providers?

In our AI consulting services, we offer tailor-made solutions specifically aligned with our customers’ individual needs. We are not tied to any particular technology and are happy to adapt to our customers’ special requirements, systems, and interfaces, so that solutions can be seamlessly integrated into existing business processes. We are so deeply involved in data science and forecasting that very little can surprise us methodologically or technologically. Accordingly, we design high-quality solutions for our customers. We also prefer to act rather than just talk. From day one, our customers get tangible results based on their own data.

Does prognostica provide support after implementation?

Yes, we are happy to support our customers after the implementation of their AI solution if desired. This includes further development, training, adjustments, and technical support. Our customers decide to what extent they make use of our support, or whether they prefer to maintain the solution themselves.