AI consulting for companies
AI Consulting That Works in Your Industry
Many artificial intelligence projects do not fail because of the technology. They fail because use cases are chosen too generically, teams are not involved and industry requirements are taken into account too late.
Ventum Consulting takes a different approach: We take an industry-specific approach and address individual challenges in your company and processes. This enables us to identify use cases that have a proven impact. The result is Artificial Intelligence (AI) initiatives that don’t get stuck in the pilot – but run productively, are used by teams and deliver measurable ROI. Our promise: Individual use cases. Structured implementation. Empowered teams.
Why Choose Ventum Consulting for AI Consulting
: Over 1,500 Projects Completed
Large corporations and small and medium-sized businesses rely on our experience because we deliver what we promise—time and time again.
Over 20 Years of Consulting Expertise at
We know the pitfalls and the shortcuts—so you can get where you’re going faster.
100% Dedicated to Your
Business Success
We aren’t satisfied until you are, because it’s the measurable results that count. That’s how we measure our success.
Strategy through
Implementation
Everything from a single source—so there are no gaps between concept and impact that cost time and money.
+1,500 projects completed
Over 20 Years of Consulting Expertise
100% Dedicated to Your Business Success
From Strategy to Implementation
- Talk directly with subject matter experts—no sales team involved
- Free Assessment of Your Situation and Needs
AI consulting use cases by industry
Every industry has its own processes, regulations, and value drivers. Generic AI solutions fail precisely because of this. We start with your industry and help identify use cases that have been proven to work there.
Here is a selection of example industries and their specific use cases involving artificial intelligence:
Industry & Manufacturing
- Predictive maintenance – detect failures before they occur. Reduce downtime costs, extend machine running times.
- AI-supported production control – dynamic order distribution based on real-time data instead of fixed rules. More throughput, more stable processes.
- Quality control with computer vision – automatically identify defects and deviations in real time – without manual inspection.
- Process optimization – reduce bottlenecks and waste with AI algorithms. Increase efficiency along the entire production line.
- Energy efficiency – intelligent control of energy flows in production and administration. Measurably reduce costs and CO₂ emissions.
- Workforce augmentation – empowering teams with AI-supported assistance systems and AR solutions. Increase productivity, mitigate skills shortages.
Automotive
- Predictive maintenance in production – analyze vehicle data, proactively identify maintenance requirements. Avoid breakdowns before they occur.
- Production optimization & robotics – Automate production processes with AI and robotics. Increase quality and efficiency.
- Simulation data management – AI readiness in engineering: Creating the basis for scalable AI in verification & validation.
- E2E Data Management – Consolidate fragmented data processes. Transparency, clear roles, higher data quality and AI readiness.
- Supply chain resilience – plan requirements with foresight, manage risks automatically. Making supply chains more resilient.
- Cybersecurity & threat detection – protecting vehicles and systems with AI-based monitoring and attack detection
Healthcare
- Diagnostics & decision support – AI-supported analysis of medical images and patient data. Increase diagnostic reliability, reduce errors.
- Administrative automation – automate documentation and billing. Relieve staff, eliminate sources of error.
- Predictive analytics & prevention – recognizing risks at an early stage, enabling targeted interventions. Shaping patient care proactively.
- Clinical workflows & AI agents – scheduling, resource management and workflow automation by autonomous agents.
- Remote Monitoring & Wearables – Monitoring chronically ill patients in real time. Reduce hospitalization rates, increase quality of care.
- Data quality & interoperability – using AI for data cleansing and system integration. Increase precision, optimize data flows.
Financial Services
- Fraud detection in real time – recognize fraudulent patterns in transactions before damage occurs. Minimize losses.
- Automated credit assessment – speed up credit decisions. Objective, data-based evaluation instead of manual checks.
- Predictive analytics for markets – analyze market trends and risks with foresight. Base investment decisions on real-time data.
- Risk management & compliance – AI for continuous monitoring of guidelines, reporting obligations and regulatory requirements.
- Dynamic pricing & product design – adapt customer-specific conditions and prices in real time. Increase competitiveness.
- Back-office automation – fully automate documents, invoices and compliance processes using AI.
Discuss use case for finance →
Logistics & Supply Chain
- Route optimization – reduce costs and delivery times. AI selects the most efficient routes, taking traffic, weather and real-time data into account.
- Demand forecasting – optimize stock levels, prevent bottlenecks. Precisely forecast requirements and seasonal peaks.
- Automated warehouses – automate storage location allocation and picking with AI-compatible robot systems.
- Real-time tracking – transparency for every shipment, at all times. AI-supported IoT data for maximum supply chain visibility.
- Supply chain risk management – proactively identify risks, develop alternative strategies with AI. Securing supply chains.
- Sustainability optimization – optimize loading capacities, routes and energy consumption for green logistics. Measurably reduce emissions.
Discuss use case for logistics →
Retail & Retail
- Personalized product recommendations – Generate individual suggestions from purchase data in real time. Increase sales and customer satisfaction.
- Dynamic price adjustment – automatically adjust prices to market and demand data. Maximize margins, secure competitiveness.
- Inventory management & forecasting – avoid overstocking and understocking. Precisely forecast demand, reduce storage costs.
- Fraud Detection – Monitor transactions and internal processes for anomalies and fraudulent activity.
- Supply chain optimization – predicting bottlenecks, optimizing transport routes, increasing transparency along all supply chains.
- Store layout optimization – data-based optimization of walkways and product placements. Increase sales per square meter.
Our AI Consulting services
Strategy, technology & implementation
AI use case identification & evaluation
We analyze your industry, processes and data situation - and identify the use cases with the highest economic leverage. Including ROI assessment, implementation readiness and prioritization.
AI Implementation & Integration
From the architecture decision to productive operation: we implement AI solutions securely in your existing IT landscape - stable, maintainable and scalable.
Proof of concept & piloting
A testable prototype with a validated business case is created in just a few weeks - so that investment decisions are based on real data, not assumptions.
Scaling & value maximization
Successful pilots are systematically rolled out to other areas, plants or markets - with a clear scaling logic and governance.
Enablement & training
AI training for teams
We enable your employees to use AI tools safely and effectively in their day-to-day work - practical, certified and immediately applicable.
Executive AI Workshops
Compact formats for managers: implementing AI strategy in your own company, evaluating priorities, managing investments. The result: decision-making capability instead of disorientation.
AI Organization & Operating Model
The development of an AI organization - from role model to embedded expertise - creates sustainable effects beyond individual pilot projects.
Change management
We ensure acceptance, skills and clear responsibilities - so that the solution is used, has an impact and investments are not wasted.
Data foundation & analytics
Data Architecture & Readiness
A scalable data architecture is the prerequisite for any productive use of AI. We create the technical and organizational basis - so that AI models run on clean, accessible data and do not fail due to fragmented systems.
Analytics & Reporting
Industry-relevant KPIs, automated dashboards and clear data flows create the transparency that operational teams and managers need to make quick, well-founded decisions.
Data-driven operations
We anchor data-based working methods in processes, roles and systems - industry-specific and scalable. The result: an organization that not only uses AI, but benefits from it in the long term.
Increased Efficiency & Cost Reduction
Through precise AI consulting, we identify process bottlenecks, reduce friction, and achieve rapid, measurable efficiency and cost benefits through AI.
Governance & Compliance
AI Governance & EU AI Act
We create guidelines, roles and verifiability - so that your use of AI is safe from a regulatory perspective and can withstand audits.
Risk & compliance management
AI risks are systematically identified, assessed and mitigated - on an industry-specific basis and with a view to applicable regulations (EU AI Act, GDPR, industry-specific standards).
Cyber Security
The development of data strategies, models and interfaces reduces operational risks and protects critical company assets.
Optimal AI Tools & Technology Stack
AI Consulting helps you select the best data and AI technologies, mitigate risks, and build a scalable technical foundation for effective AI solutions.
Your AI Consulting Experts
Success Stories - Successful AI consulting projects from Ventum Consulting
Scaling AI Adoption Across the Enterprise: From AI Pilots to Production Deployment
AI was used sporadically, but not systematically integrated into work processes – a uniform level of competence and scalable methodology were lacking.
Our Approach
A modular enablement program ranging from AI fundamentals and structured prompting to full Copilot integration into the operational toolchain.
Result
-wide adoption of Copilot across all key workflows. Measurably higher efficiency in documentation, task management, and daily planning.
Key to Success
: End-to-end integration into existing business processes rather than isolated tool training. To the success story
AI in Controlling: Transforming Analysis, Forecasting, and Management Reporting
Controllers from several companies were looking for a systematic way to integrate AI into analysis, planning, and reporting beyond individual experiments.
Our Approach
A domain-specific AI program designed around real-world controlling processes—from automated commentary and forecast support to AI-driven management storylines.
Result
Significant time savings in reporting. Greater consistency in management reports. Initial standardized AI workflows established across the entire organization.
Success factor
Precise alignment with the value chain of controlling – with immediately applicable results. To the success story
Building AI Readiness: From Understanding to the Productive Use of Agents and Automation
A newly established department needed a robust AI foundation within a short period of time—not theory, but the ability to take productive action.
Our Approach
Structured skill development ranging from LLM understanding and prompting methodology to agent-based workflows and end-to-end automation.
Result
A consistent understanding of AI, independent use of prompting and AI agents from day one, and noticeably higher efficiency in day-to-day operations.
Key to Success
Not merely imparting knowledge, but fostering the ability to take action—from initial orientation to the next stage of maturity. To the success story
AI-Based Production Optimization: From Bottleneck Analysis to Real-Time Decision Support
: Bottlenecks on the production line were holding back capacity utilization and output—the complexity of the equipment, production program, and data quality made conventional optimization impossible.
Our Approach
On-site process analysis, data-driven identification of improvement potential, and development of an AI-powered real-time simulation for dynamic feed optimization—based on live production data.
Result
Over 5% increase in output during normal operation, up to 8% in critical high-load situations—while simultaneously transferring know-how to the customer’s employees to ensure sustainable implementation.
Key Success Factor
In-house development instead of a standard solution—deep process understanding combined with AI, mathematical optimization, and real-time data. To the success story
AI in IT Governance: From Manual Compliance to Automated Corporate Management
: Growing compliance requirements, redundant documentation obligations, and a lack of transparency regarding IT services made manual governance increasingly inefficient, error-prone, and unscalable.
Our Approach
Group-wide analysis of governance processes, development of a user-centered “Governance as a Service” framework with a semantic data model, and piloting of AI-driven automation for machine-readable, compliance-compliant documentation.
Result
Digitized, automated governance processes with full transparency regarding status, risks, and regulatory requirements—scalable, flexibly adaptable, and ready for immediate rollout.
Key Success Factor
Governance consistently designed from the user’s perspective—combined with AI automation and a scalable data model instead of rigid, document-based frameworks. To the success story
AI Readiness in Engineering: Simulation Data Management as the Foundation for AI in Product Development
: Over 16 simulation disciplines with varying data requirements, a lack of integration between geometric and functional data, and no AI-enabled data structures—all while aiming for a rollout to over 2,500 employees.
Our Approach
Systematic requirements analysis across all disciplines, development of validated use cases, and a scalable architectural vision for cross-functional simulation data management—serving as the direct foundation for AI agents and machine learning.
Result
AI-enabled data structures established, a viable architectural concept for non-geometric data derived, and modern workflows embedded—scalable from a pilot team to an industrial rollout.
Key Success Factor
In-depth engineering expertise combined with data-driven architectural expertise—not AI for AI’s sake, but the right data foundation as a prerequisite for genuine AI benefits. To the success story
Data-Driven Feature Management: From Idea to Market-Ready Innovation in Record Time
Rising customer expectations, limited budgets, and a lack of data-driven management of the feature pipeline made it difficult to prioritize digital innovations and bring them to market in a timely manner.
Our Approach
A structured gate and feature funnel process with a data-driven evaluation system, a maturity catalog, and real-time reporting—focused on customer value and cost-effectiveness.
Results
: 30% more features released, reduced rework, and faster time-to-market. Investments are directed specifically toward the most impactful innovations—from concept to over-the-air update.
Key Success Factor
: Cross-functional feedback loops and full transparency regarding budgets, resources, and maturity levels. To the success story
E2E Data Journeys: Transforming Fragmented Data Management into a Controllable Framework
Inconsistent practices, a lack of collaboration between data providers and users, and a fragmented architecture led to redundancies and a lack of controllability – over 30 overlapping processes with more than 250 process steps.
Our Approach
: Development of an “E2E Data Journey” as an analytical template for harmonizing existing frameworks—from an “as-is” analysis through user-centered target design to a gap analysis with an implementation plan. Consolidated within 2 months.
Result
A harmonized, company-wide data management framework with clear responsibilities, standardized processes, and AI-enabled data structures—the foundation for scalable AI use cases.
Success factor
Data requirements are consistently derived from the business strategy rather than conceived from IT – lightweight and quickly scalable. To the success story
From industry analysis to the scaled use of AI - how AI consulting works at Ventum Consulting
A one-size-fits-all approach to AI consulting doesn’t work. That’s why we tailor our approach precisely to your industry, your level of maturity, and your business goals—with clear phases and measurable results at every stage. We always start with a deep understanding of your industry and the AI use cases that have proven effective there. Building on this, we evaluate and prioritize the most promising use cases based on ROI potential, data availability, and implementation effort—ensuring that investment decisions are based on reliable figures. Even before the first model is developed, we lay the necessary groundwork in terms of data and architecture and, within a few weeks, use this to develop a proof of concept that demonstrates the expected benefits under real-world conditions.
Only after this validation does the productive rollout into your IT landscape take place, along with the parallel training of your teams—to ensure that the solution is actually used in day-to-day operations. Governance and compliance guide the entire process from the very beginning. And as soon as the first use case demonstrates its value, we systematically apply proven methods to additional processes, locations, and markets.
AI training & education from Ventum Consulting
AI expertise is not a nice-to-have – it is the difference between a pilot that collects dust on the shelf and a solution that creates value every day.
Our training courses, including in the field of artificial intelligence, are industry-oriented, practical and tailored to specific roles. No abstract theory – just methods and tools that your employees will be able to use tomorrow.
Training courses at a glance:
Agentic Coding Training - AI app development process
Participants will learn how to transform the entire software development lifecycle into a systematic, reproducible process using AI-powered agent tools —from precise requirements specifications and the automatic generation of source code to quality control and scalable deployment. The goal is to reduce development effort and significantly increase productivity.
AI Security Assessment
With the AI Security Assessment, you’ll receive a comprehensive, well-founded evaluation of your AI infrastructure—including identified security vulnerabilities, risks prioritized by urgency, attack scenarios tested under real-world conditions, and a transparent, verifiable action and governance roadmap that ensures your AI applications are secure, compliant, and scalable as they are deployed into enterprise-wide production operations.
Application Modernization & Migration Workshop
This workshop focuses on methodically analyzing complex legacy systems, transforming them into a future-oriented architectural and operational structure, and, building on that foundation, developing concrete modernization and migration strategies—with the goal of achieving more stable systems, reduced risks, and a technologically up-to-date, AI-ready application environment.
ChatGPT & Copilot training - save time with AI and prompt engineering
Hands-on application of ChatGPT and Microsoft Copilot to achieve lasting productivity gains in day-to-day work.
ChatGPT training - using AI professionally in everyday work
Turn repetitive tasks into well-thought-out prompts, increase efficiency, and consciously use AI as a supportive tool.
Design sprint for AI - from business case to prototype in 5 days
Within five days, an artificial intelligence (AI) concept is transformed into a testable prototype with a validated business model. Perfect for teams that want to drive innovation and make well-informed investment decisions.
AI Champion Training
In this training program, employees and managers develop the skills to use artificial intelligence confidently, identify relevant AI opportunities within the company, and actively support change processes. The AI Champion training program combines practical AI knowledge with strategic implementation, governance, and change management—ideal for companies that want to embed AI sustainably and build internal expertise in a targeted manner.
AI workshop - Develop your own use cases
Systematic identification, assessment, and prioritization of industry-specific artificial intelligence (AI) use cases. The result: a concrete roadmap with a profitability assessment and defined follow-up actions.
AI workshop for SMEs
An application-oriented introduction to artificial intelligence with a focus on business implementation and scalability. Ideally suited for medium-sized companies seeking to achieve tangible value creation.
AI workshop for companies - successfully anchoring innovation
A well-founded analysis of current AI methods and their targeted application in business practice. Ensures transparency, confidence in decision-making, and a solid foundation for systematic implementation.
Related Articles on Artificial Intelligence (AI), Data, and More
Arrange a non-binding initial consultation now
- Future-oriented: Using the potential of AI as a targeted growth driver
- Tailor-made: Individual AI solutions for your specific challenges
- Proven: Over 20 years of practical experience from successful projects guarantees reliability
- Strong implementation: from conception to measurable realization of results
- Value-oriented: Clear focus on sustainable benefits and real competitive advantages
TISAX and ISO certification apply only to the Munich location
Your message
FAQs on the topic of AI Consulting
We advise companies from a wide range of sectors, such as industry & manufacturing, automotive, financial services, healthcare, logistics & supply chain and retail (excerpt) – with use cases that have been proven to work in these sectors.
That depends on the scope. A use case workshop is completed in one day. A proof of concept typically takes 4-8 weeks. Full implementations usually take 3-6 months. We always recommend starting with a clearly defined first step when using artificial intelligence.
Yes – and this is a central component of our approach. We offer certified training courses (e.g. ChatGPT, Copilot, Prompt Engineering), industry-specific workshops and individual curricula for different roles. For us, enablement is not an add-on, but part of every project.
The costs depend on the scope, duration and team size. We recommend a use case workshop or a non-binding initial consultation to get started – so that you can quickly obtain a realistic assessment.
Three things: Firstly, we always start with your industry and your processes – not with generic frameworks. Secondly, we integrate team enablement right from the start. Thirdly, we don’t deliver strategy papers that end up in a drawer – we support you right through to productive operation.
Governance and compliance are not an afterthought for us – they are considered right from the start of the project. We create guidelines, roles and verifiability in accordance with the EU AI Act, GDPR and industry-specific standards (e.g. MDR in the healthcare sector, regulatory requirements in the finance sector).