Many companies feel the pressure to use AI meaningfully – and at the same time face the same hurdles:
The crucial bottleneck is rarely in the technology.
It lies in realistically evaluating data before investing.
You don't know where and how to start with AI in your company
AI solutions seem too technical and difficult to understand
You lack internal capacities and technical know-how
You shy away from the high costs without certainty about the benefits
AI solutions seem too technical and difficult to understand
The AI Readiness Audit provides you with a structured analysis of your production and process data. The goal is not a theoretical AI concept, but a concrete decision-making basis.
We check where your data stands today, which use cases are realistic and which next step makes economic sense – for example in the areas of Pattern Detection, Anomaly Detection or Root Cause Analysis.
At the end you know:
In comparable projects, we have developed AI-based analysis solutions to make production processes more transparent and to make potential improvements visible.
Among other things, Python-based methods for pattern recognition on sensor and process data were used. The result was a scalable analysis approach that served as the basis for reducing scrap and downtime.
The focus was not on a large AI project, but on a stable, comprehensible entry.
✓ Automatic summary of meetings
✓ Creation of offers and presentations
✓ Analysis of customer data and reports
✓ Support with e-mail communication
The AI Readiness Audit is clearly structured and delivers tangible results:
Evaluation of your existing data sources with regard to quality, availability and technical feasibility.
Documentation of data gaps, dependencies and technical risks – understandable for IT and management.
A concrete design of how AI can be used in your systems or processes.
A realistic plan for a first prototype with manageable risk and clear benefits.
We combine strategic proximity with technical depth.
You will be personally supported by our team in Germany – with clear communication and reliable commitments. The implementation is carried out by our specialized engineering team in Bratislava, with expertise in Python, Java and modern web technologies.
Our way of working combines precision, reliability and industrial reality. No consulting product, but engineering thinking.
On request, we invite you to get to know our team on site and gain insight into our way of working.
Before AI can be used meaningfully, a realistic picture of the initial situation is needed. We analyze processes, data availability, system landscape and organizational requirements. This reveals how AI can be effective today – and which gaps need to be closed first.
Not every AI idea is useful, not every use case is ready for implementation. Based on the analysis, we evaluate concrete applications according to benefit, feasibility and risk. The result is a prioritized view of where AI delivers real added value and where it currently generates more effort than impact.
In the end, there is no tool recommendation, but clarity. You will receive a reliable basis for decision-making with clear options: What makes sense now. What should be prepared. And what can consciously wait. Especially for industrial companies, this means: controlled decision-making instead of experimenting on suspicion.
While many competitors communicate AI in a technically complicated way, we focus on simple, quickly implementable and understandable solutions.
We do not develop AI models from scratch, but make existing AI technologies usable for you. This is faster and more cost-effective.
We understand the needs of medium-sized companies and offer solutions that fit your budget and resources.
Through the consistent use of AI in our own development, we are faster and more efficient than traditional providers.
For companies that want to seriously test AI, but do not want to invest on suspicion. Especially for organizations with grown system landscapes, complex processes or regulated environments in which incorrect decisions are expensive.
It is deliberately an upstream phase. The goal is clarity and decision-making ability. Whether a concrete AI project emerges from this will only be decided on the basis of the results.
No. That’s exactly what we clarify together. Often, the analysis reveals where data is available, where it is missing and which prerequisites can be realistically established.
As deep as necessary, not deeper than makes sense. We look at processes, system architecture, data flows and organizational frameworks without slipping into unnecessary detail or theoretical models.
The focus is clearly on companies with operational complexity, such as from industry, mechanical engineering or regulated industries. However, the approach works wherever AI has to be integrated into existing IT.
Not across the board. If tools make sense, we will name them. Often, however, the more important realization is which prerequisites should be created first before tool decisions are made.
Usually a few weeks. The goal is a compact but well-founded basis for decision-making – not a months-long analysis project.
A clear classification of your AI maturity level, prioritized use cases, a realistic assessment of benefits and effort as well as concrete recommendations for action for the next steps.
No. The results are freely available to you. If you would like to continue working with us afterwards, all the better. If not, you have still gained clarity.
Because our view comes from the implementation. We have been developing complex software and cloud solutions for years and know what works in real system landscapes and what doesn’t.
Together, we will check your needs, show you technical options and say honestly whether – and how – Riwers will move you forward.