Strategically implementing artificial intelligence in the company

AI Consulting for Businesses

Leverage the potential of artificial intelligence in a targeted way for your processes, data, and business models.

NOVUSTAT helps you identify suitable AI use cases and evaluate their business potential. Together, we develop a customized AI strategy and guide you through the entire process—from an AI potential assessment to initial pilot projects and implementation. In doing so, we take into account your existing processes, data flows, and data quality, as well as technical requirements, governance, and compliance.

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NOVUSTAT in a nutshell

Experience, expertise and quality

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Dr. Robert Grünwald

CEO & Founder NOVUSTAT GmbH

Profile of Dr. Robert Grünwald, CEO and Founder of NOVUSTAT
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What is AI consulting?

Professional AI consulting helps companies systematically identify the potential of artificial intelligence and translate it into concrete, economically viable use cases. The focus is not solely on the technology itself. What matters most is determining which processes can actually be improved or automated and what measurable added value the use of AI can create for the company.

To begin, we analyze your existing processes, data flows, and technical requirements together. An AI potential assessment helps identify and prioritize suitable use cases and evaluate them in terms of benefits, effort, and feasibility. These may include process automation, document processing, forecasting, data analysis, intelligent assistance systems, or applications in customer service and back-office operations.

Based on this, we develop an AI strategy. Depending on the specific use case, implementation can initially take place as part of a pilot project. This allows an AI solution to be tested and evaluated under realistic conditions before it is integrated into existing processes and technology architectures or scaled company-wide.

Successful implementation of AI also requires that technical and organizational conditions be taken into account. These include, in particular:

  • Data Quality and Data Flows: Check the availability, structure, and quality of the required data
  • Use Cases: Prioritize AI potential based on economic value and technical feasibility
  • Technology and Integration: Select appropriate models, systems, and technology architectures
  • Governance and Compliance: Take responsibilities, protection requirements, and regulatory requirements into account
  • Skills development: Prepare employees for the practical use of new AI solutions

 

This turns an initial idea into a structured path from potential analysis through the pilot project to implementation and scaling of a viable AI solution.

From AI strategy to successful implementation

Professional AI consulting for strategy, use cases, and implementation

NOVUSTAT supports companies in the structured adoption and use of artificial intelligence. Our AI consulting ranges from an initial potential assessment and the selection of suitable use cases through pilot projects to technical implementation and scaling. We tailor strategy, data, processes, and technologies to your requirements and business objectives.

  • AI potential assessment for processes, data, and existing systems
  • Development of a custom AI strategy for your company
  • Identify and prioritize suitable AI use cases
  • Assessing the Economic Viability and Technical Feasibility of AI Projects
  • Design pilot projects to test specific AI solutions
  • Process automation for recurring tasks and workflows
  • AI-powered document processing and information retrieval
  • Analyze data quality and data flows for AI applications
  • AI solutions for customer service and back-office operations
  • Enabling AI-based forecasts and data-driven decisions
  • Select and implement suitable machine learning algorithms
  • Integrate AI solutions into existing technology architectures
  • Consider governance, compliance, and protection requirements in AI projects
  • Scaling and Further Developing Successful AI Applications
  • Skills development for the sustainable use of AI in the company
  • Support from concept development through implementation and execution
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Regina Hollweck

Senior Statistician

Regina Hollweck, Senior Statistician at NOVUSTAT, is the contact person for statistical consulting and a free initial assessment.
Free Initial Assessment

Do you need support with
AI consulting?

We would be happy to support you with AI consulting and the successful implementation of artificial intelligence in your company. NOVUSTAT analyzes your processes, data, and technical requirements and shows you which AI use cases are economically viable and technically feasible. Together, we develop the right path from the initial potential assessment to implementing your AI solution.

+49 (0) 211 99346512
+41 (0) 78 89 11111
United States
+1 (888) 5233685
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Benefits of AI consulting for your company

With professional AI consulting you lay the foundation for using artificial intelligence not only selectively, but strategically and economically. NOVUSTAT helps you improve processes, use existing data more effectively, and turn suitable AI use cases into viable solutions.

Make processes more efficient

Identify recurring and time-consuming workflows that can be simplified through AI and process automation . This can reduce employees' workload and make internal processes more efficient.

Use data more effectively

Use existing company data more systematically for analyses, forecasts, and data-driven decisions. We also take data quality, data flows, and the requirements for reliable AI use into account.

Reduce costs and effort

Automated document processing, intelligent assistance systems, and AI-powered back-office processes can reduce manual steps and make resources available more effectively.

Improve customer service

AI can process customer inquiries more quickly, provide information, and support customer service staff. Detailed Customer Analytics can also help you better understand needs and behavioral patterns.

Make better-informed decisions

AI-based models can analyze complex data volumes, identify patterns, and generate forecasts. This gives companies additional information for operational and strategic decisions.

Build competitive advantages

By identifying suitable use cases early, running pilot projects, and building structured expertise, new technologies can be integrated sustainably into the company and create long-term competitive advantages.

Specific use cases for businesses

Practical examples of AI applications

AI delivers the greatest value where concrete processes, data, and business requirements are the focus. NOVUSTAT helps you identify suitable AI use cases and turn them into practical solutions. Applications range from process automation and document processing to forecasting, customer analytics, intelligent assistance systems, and data-driven decision-making processes.

AI Solutions & Assistants

AI-powered assistants can support employees with recurring tasks, information searches, and customer service. This makes it possible to automate routine processes, reduce manual back-office tasks, and streamline existing workflows.

AI Forecasting

AI-based forecasts help companies derive future developments from existing data. Depending on the use case, demand, sales, utilization, or other metrics can be modeled and used as a basis for data-driven decisions.

Document & Pattern Recognition

AI can automatically identify, read, and process structured, semi-structured, and unstructured information. Typical use cases include document processing, classification, pattern recognition, and extracting relevant content from large datasets.

AI in Human Resources

In human resources, AI can support administrative processes, structure application and profile data, and reveal training and skills needs. This can reduce employees' workload and better support data-driven decisions in HR processes.

AI in Marketing & Customer Analytics

In marketing, AI supports the analysis of customer behavior, segmentation, and campaign optimization. Combined with Customer Analytics , patterns along the customer journey can be identified and measures targeted more effectively.

Tailored, flexible, and aligned with your business

AI consulting for businesses of every size

NOVUSTAT supports companies, teams, and decision-makers in implementing and advancing AI solutions. Our consultants combine experience in Data Science, Machine Learning and data-driven processes with a practical perspective on your specific requirements. Before starting, we analyze your initial situation, define suitable use cases, and tailor the scope of consulting to your needs.

AI consulting can be delivered entirely online, making it flexible and independent of your location. Depending on the project, we support you selectively with individual questions or across several phases—from the potential assessment and pilot project to implementation and scaling.

Tailored to your business
Consulting based on your processes, data, objectives, and existing technology.
Flexible and location-independent
Online consulting for companies in Germany, Austria, Switzerland, and beyond.
Transparent costs before the project starts
The scope and cost of consulting are agreed individually and transparently before work begins.
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How your AI consulting engagement with NOVUSTAT works

From the initial idea to successful implementation

From initial potential analysis through implementation, we guide you systematically through every project phase. Together, we identify suitable use cases, review data and technical requirements, and develop a viable AI solution for your company.

01
Phase 01 of 04
Understand the starting point.
Analyze potential and requirements

At the outset, we examine your business objectives, existing processes, available data, and technical environment. Together, we assess where AI can create tangible value and which requirements must be met for successful implementation. This creates a solid foundation for the broader AI strategy and the selection of suitable use cases.

02
Phase 02 of 04
Evaluate use cases strategically.
Prioritize AI use cases

Based on the analysis, we identify and evaluate specific AI use cases. We consider economic value, technical feasibility, data quality, protection requirements, and expected implementation effort. We then prioritize the use cases that promise the greatest strategic and operational value for your company.

03
Phase 03 of 04
Test and validate the solution.
Develop and test a pilot project

For a prioritized use case, we develop a suitable pilot project. The AI solution is tested under realistic conditions and evaluated against defined criteria. We examine data flows, model quality, process integration, and practical usability before deciding on further implementation.

04
Phase 04 of 04
Embed AI sustainably in the company.
Implement and scale

Following successful validation, we support the integration of the AI solution into existing processes and technology architectures. We take governance, compliance, responsibilities, and the necessary skills development into account. The goal is a stable, scalable solution that can be used permanently in your business operations and further developed as needed.

01 Analyze potential
Phase 01 of 04
Understand the starting point.

Analyze potential and requirements

At the outset, we examine your business objectives, existing processes, available data, and technical environment. Together, we assess where AI can create tangible value and which requirements must be met for successful implementation. This creates a solid foundation for the broader AI strategy and the selection of suitable use cases.

02 Prioritize use cases
Phase 02 of 04
Evaluate use cases strategically.

Prioritize AI use cases

Based on the analysis, we identify and evaluate specific AI use cases. We consider economic value, technical feasibility, data quality, protection requirements, and expected implementation effort. We then prioritize the use cases that promise the greatest strategic and operational value for your company.

03 Test pilot project
Phase 03 of 04
Test and validate the solution.

Develop and test a pilot project

For a prioritized use case, we develop a suitable pilot project. The AI solution is tested under realistic conditions and evaluated against defined criteria. We examine data flows, model quality, process integration, and practical usability before deciding on further implementation.

04 Implement & scale
Phase 04 of 04
Embed AI sustainably in the company.

Implement and scale

Following successful validation, we support the integration of the AI solution into existing processes and technology architectures. We take governance, compliance, responsibilities, and the necessary skills development into account. The goal is a stable, scalable solution that can be used permanently in your business operations and further developed as needed.

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How do artificial intelligence and machine learning work?

Foundations of modern AI systems

Artificial intelligence encompasses various technologies and methods that enable computer systems to perform complex tasks using data. Machine Learning is a key foundation for many of today’s AI applications. The methods used depend on the available data, the specific use case, and the desired outcome.

What is artificial intelligence?

Artificial intelligence enables systems to perform tasks such as recognizing, evaluating, predicting, and deciding using data.

AI can analyze large volumes of data and identify patterns, relationships, and relevant information.

Use cases range from AI assistants and forecasts to document processing and process automation.

The appropriate AI solution depends on the use case, data quality, and business objectives.

How does machine learning work?

Machine Learning is a central method for developing data-driven AI systems.

Models are developed, tested, and optimized step by step using existing training data.

Learned relationships can then be applied to new and previously unseen data.

Typical applications include forecasting, classification, pattern recognition, and customer analytics.

The selection of suitable machine learning algorithms depends on the data structure and objective.

What learning methods are available?

Supervised Learning: Training with known target values, for example for forecasting and classification.

Unsupervised Learning: Identifying unknown structures, groups, and patterns without predefined target values.

Reinforcement Learning: A system learns by evaluating its decisions and the resulting outcomes.

The appropriate learning method depends on the use case, available data, and desired outcome.

Data quality, model selection, training, and validation are essential for reliable models.

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Frequently asked questions about AI consulting

Which companies benefit from AI consulting?

AI consulting is suitable for companies that want to identify concrete opportunities for artificial intelligence, improve existing processes, or develop new data-driven solutions. This can involve individual use cases as well as a comprehensive AI strategy, pilot projects, or the introduction of new technologies.

How does an AI consulting engagement with NOVUSTAT begin?

At the outset, we analyze your objectives, processes, data flows, and technical requirements. An AI potential assessment helps identify suitable use cases and prioritize them by value, feasibility, and effort. Based on this, we agree on the next steps for consulting and implementation.

Which AI use cases can we advise on?

Typical use cases include process automation, document processing, forecasting, customer service, back-office operations, customer analytics, and intelligent assistance systems. The right solution depends on your data, processes, objectives, and existing technology architecture.

What role do data quality and data flows play?

Data quality and stable data flows are key requirements for reliable AI solutions. We therefore assess which data is available, how it is structured, and whether it is suitable for the intended use case. If necessary, this can be complemented by statistical consulting.

Does NOVUSTAT also support machine learning projects?

Yes. Depending on the question, we support the selection of suitable models, the development of forecasts, and the evaluation of technical approaches. You can also find an overview of common methods in our article on machine learning algorithms.

What is the difference between a pilot project and implementation?

A pilot project is used to test a prioritized AI use case under realistic conditions. Implementation in existing processes and systems only follows once the value, model quality, and technical feasibility have been sufficiently validated. This approach helps reduce project risk.

How are governance, compliance, and protection requirements addressed?

When introducing AI, we consider governance, compliance, responsibilities, and protection requirements alongside the technical implementation. The goal is an operating model in which the use of technology is governed transparently and AI solutions can be developed and scaled in a controlled manner.

Can AI also be used in marketing and customer service?

Yes. AI can support customer inquiries, segment customer groups, analyze behavior, and optimize marketing activities using data. Our article on Customer Analytics.

When is reinforcement learning appropriate?

Reinforcement learning can be useful for selected decision problems in which a system gradually learns a strategy through feedback on its actions. You can find more information in our article on Reinforcement Learning.

How much does AI consulting cost?

Costs depend on the scope, complexity of the use cases, and the level of support required. A potential assessment involves a different effort than developing an AI strategy or supporting a pilot project through implementation. Before the project starts, you receive an individually tailored and transparent proposal.