AI Consulting: Strategy & Implementation

This depends on your current situation and where a concrete result can be achieved most quickly. If a tool is already in use, we build automations directly on it, leveraging your existing investment. If a process needs to be automated, we select the appropriate tool and implement it productively. Not as a pilot, but as a solution that provides relief from day one. If it's still unclear where the greatest impact can be made, the QuickCheck is the fastest way to start: 1.5 days of inventory, resulting in two to three prioritized processes.

Simple workflows in Power Automate or n8n are often live within two to four weeks, including testing and handover. This means you see a return before the quarter ends. More complex processes involving AI components, multi-system integration, or data preparation take longer, but the impact is usually greater in the end. During the initial consultation, we'll assess the effort, benefits, and time to go live for each process.

We are technology-agnostic. Power Automate, n8n, and Copilot Studio are our primary tools because each has different strengths. We don't recommend the tool that best suits us, but the one that brings you the most benefit. We choose based on your infrastructure, data situation, and the process to be automated. If another tool is a better fit, we'll tell you.

You decide. Either you operate the solution yourselves, and we'll hand it over with clear documentation and train your team. Or we'll handle monitoring, maintenance, and scaling. During the access phase, we set up governance, logging, and alerts, and empower your team to independently maintain simple workflows later on. This way, you remain independent and don't have to call us for every minor adjustment.

More than many expect. An automated process is only as good as the data it processes. Faulty master data produces erroneous results, just faster and on a larger scale. Nobody wants that. Because we come from data consulting, we first look at the data foundation for every automation. If it's flawed, we'll get it into shape if necessary before building the solution on top of it. This way, you get a result you can trust from day one.

Agentic AI refers to software that doesn't just react to individual commands but autonomously takes on tasks. It understands context, makes decisions, and executes multiple steps consecutively without anyone initiating each click. For example, an AI agent can read a customer inquiry, check the CRM, formulate and send the appropriate response, while your team focuses on tasks requiring human judgment. The practical difference from traditional automation: instead of automating individual steps, an agent handles the entire process.

Repetitive tasks are handled by software, automatically, reliably, 24/7. Humans define what should happen. The software executes it, even at night, on weekends, and without sick leave. The result: reclaimed time, eliminated errors, and capacity that grows with your business.

RPA is purely rule-based and reaches its limits when a process requires understanding rather than fixed instructions. For example, when reading documents, classifying free text, or handling edge cases. Modern automation connects systems directly via APIs and uses AI for decisions that cannot be mapped with rules alone. For you, this means significantly more processes become automatable, including those where traditional RPA has previously failed.

Power Automate is closely integrated with Microsoft and works seamlessly with Teams, SharePoint, Outlook, and Dynamics. It's ideal if your stack runs on M365 and you're looking for quick wins within your existing infrastructure. n8n is open source, self-hostable, and more flexible for complex API integrations with systems outside the Microsoft ecosystem, including full data and hosting control. Which one fits depends on your stack and how much data control you need. We'll help you figure that out during an initial consultation.

Traditionally, processes that are repetitive, rule-based, and time-consuming are well-suited. This includes invoice processing, report generation, and approval workflows. With AI, applications that require unstructured data are added: reading documents, classifying free text, and categorizing requests. As a rule of thumb, if someone in your team performs the same step multiple times a day, it's worth investigating. The same applies if a process regularly stalls because no one has time. That's often where the biggest impact is made.