AI Consulting
AI Strategy & Transformation
We help companies understand how artificial intelligence can support their business model, strategic goals, and operational priorities. This starts with identifying the most relevant opportunities and defining a realistic path from current maturity to future AI-enabled business capabilities.
Our consulting covers AI maturity assessments, strategic roadmaps, use case prioritization, business case development, ROI evaluation, and decision support for management teams. We help organizations move beyond fragmented pilots and develop a structured AI transformation approach that creates measurable value and supports sustainable adoption across departments and business units.
- AI maturity assessment and transformation roadmap
- Use case prioritization by impact, feasibility, and ROI
- Business model analysis and executive decision support
AI Process Integration
We analyze existing business processes and identify where artificial intelligence can improve speed, quality, consistency, and cost efficiency. The goal is not to introduce AI for its own sake, but to improve concrete business workflows in a practical and manageable way.
This includes process mapping, workflow analysis, automation concepts, and the integration of AI into operational processes such as finance, HR, customer service, procurement, retail operations, and back-office environments. We also support intelligent document processing scenarios such as invoice handling, contract analysis, form extraction, and classification workflows.
- Automated accounting and transaction validation
- AI-based application filtering and candidate ranking
- Intelligent document processing for invoices and contracts
AI Use Case Development
We identify, evaluate, design, and prepare tailored AI use cases that align with business needs and produce measurable outcomes. Many organizations know they want to use AI, but they need support to translate broad ideas into practical initiatives with real business value.
We help define concrete use cases, assess feasibility, evaluate risks, estimate benefits, and structure implementation plans. Our work spans a wide range of domains such as customer service automation, predictive analytics, computer vision, energy forecasting, medical support scenarios, quality control, intelligent search, and advanced decision support. The result is a clear and actionable path from idea to execution.
- Use case discovery and feasibility assessment
- Pilot and MVP design for high-value scenarios
- Implementation planning focused on business outcomes
AI Architecture & Infrastructure
A successful AI initiative requires the right technical foundation. We advise companies on how to design AI architecture and infrastructure that fit their business, security, compliance, performance, and scalability requirements.
This includes cloud, on-premise, hybrid, and edge deployment models as well as GPU planning, model serving, data pipelines, storage concepts, orchestration, and integration architecture. We support clients in selecting the right setup for enterprise AI workloads, including compliance-sensitive environments where data sovereignty, access control, latency, or reliability are critical factors.
- Cloud, on-premise, and hybrid architecture patterns
- Edge AI deployment and real-time processing
- Scalable model serving and data pipeline design
EU AI Act & Governance
Artificial intelligence needs more than technical capability. It also requires governance, transparency, accountability, and compliance. We support organizations in building AI systems and operating models that are aligned with regulatory and ethical requirements.
Our consulting includes AI system inventories, risk classification, governance frameworks, technical documentation support, transparency requirements, human oversight concepts, post-market monitoring, incident management preparation, and AI literacy enablement. We also help align AI initiatives with GDPR and internal compliance standards. This is especially important for companies operating in regulated sectors or in the European market.
- AI system inventory and risk classification
- GDPR and EU AI Act dual compliance alignment
- Technical documentation, oversight, and monitoring
Scaling & MLOps
Many AI initiatives fail because they remain stuck in proof-of-concept mode. We help companies move from isolated pilots to stable, production-ready, and scalable AI operations.
This includes the design of AI operating models, rollout concepts, monitoring strategies, retraining mechanisms, model lifecycle management, performance governance, KPI frameworks, and business value tracking. We support the structures and processes needed to deploy AI across teams, regions, plants, or business units in a reliable and controlled way.
- Production scaling from proof of concept to enterprise rollout
- Monitoring, drift detection, and retraining
- KPI frameworks and AI operating models
Knowledge & Agentic Automation
We help organizations unlock the value of their internal knowledge and connect it with intelligent automation. This enables employees, teams, and functions to access information faster, reduce manual effort, and improve decision quality.
Typical solutions include enterprise knowledge assistants, internal support bots, proposal support tools, contract review assistants, service desk automation, and workflow agents that operate across business systems. These solutions can be built with strong access control, secure retrieval, and department-specific context so that they fit real enterprise environments.
- Enterprise knowledge assistants and RAG foundations
- Workflow agents for service, sales, marketing, and legal
- Cross-system automation with secure access controls
Data & Model Operations
Reliable AI depends on reliable data and controlled model operations. We support companies in building the data, process, and lifecycle foundations that keep AI systems accurate, maintainable, and cost-efficient over time.
Our services include data pipeline design, data preparation, annotation concepts, governance controls, fine-tuning support, retraining strategies, synthetic data approaches for privacy-sensitive use cases, and model lifecycle management. We help ensure that AI systems are not only deployed, but also sustained and improved in a structured way.
- Data pipelines, labeling, and data governance
- Fine-tuning, retraining, and lifecycle management
- Synthetic data options for privacy-sensitive scenarios