Robotic process automation for efficient business processes

A good RPA candidate is clearly rule-based, runs frequently, always follows the same steps and uses digitally readable inputs. The more exceptions, judgement calls or media breaks, the worse the fit. We assess your processes by volume, rule stability and error cost—grounded in /en/services/process-mining or a discovery workshop, before any licences are bought.

Partly: automating a chaotic process only cements the chaos. We handle small clean-ups directly in the design and make larger structural issues visible instead of hiding them. Often only the analysis via /en/services/process-mining reveals where standardisation pays off—and where a bot delivers value immediately.

We almost always recommend the pilot: one high-volume process with clear rules and measurable benefit. Once pilot and KPIs hold, we scale to more bots and departments in a controlled way. This avoids costly misinvestments and builds solid internal arguments. For a first assessment use /en/project-check.

RPA is no longer just for large corporations. In the mid-market, bots pay off as soon as repetitive manual work occurs regularly—such as invoice intake or master data maintenance. What matters is process volume, not company size. For lean scenarios, /en/services/power-automate or /en/services/n8n-workflows are often the more economical choice.

We advise vendor-neutrally: UiPath excels at fast development and desktop automation, Blue Prism at strict enterprise governance in regulated industries. For lighter workflows, Power Automate or open-source tools may suffice. We decide by IT landscape, licence budget and team skills—not by tool hype. Overview: /en/services/automation.

Beyond one-time bot development, there are recurring platform and licence costs (depending on bot count and term) plus maintenance effort—for example when target applications change. We factor these follow-up costs in from the start. For a realistic total view with ROI, use /en/costs/rpa-roi and /en/costs/automation.

For good results we need access to the target systems, contacts in the business unit and clarity on the business rules including edge cases. We handle the technical build, error handling and documentation. The more precisely you can describe the target process, the faster and more stable the bot runs in production.

Yes. We document every bot so IT and business can trace changes—without dependency on a single developer. On request we train your team and build a Center of Excellence with standards and templates so you maintain and scale bots yourselves. Alternatively, we provide maintenance and hypercare on an ongoing basis.

We give every bot clean error handling, restart logic and logging. Via the Orchestrator or Control Room we run monitoring, alerts and defined escalation paths—if a job fails, it is reported and can be resumed in a controlled way. So no bot runs blindly in the background, and your team always knows what happened.

Bot sprawl arises without governance. From day one we rely on central control via the orchestrator, consistent standards, versioning and a Center of Excellence. Every bot is documented, assigned an owner and traceable through audit logs. So you scale in a controlled way instead of with undocumented scripts on single PCs. Strategic frame: /en/services/automation.

Not necessarily. RPA bridges the phase where stable interfaces are still missing or uneconomical. In parallel we plan—where sensible—the replacement with APIs so you do not depend on UI automation forever. With an ERP replacement, we then move the logic cleanly onto interfaces. Background: /en/comparisons/rpa-vs-api-integration and /en/services/api-integration.

We define measurable KPIs before rollout—such as saved processing hours, error rate and lead time—and measure them in the pilot against the manual baseline. This produces a solid business case for internal approvals. You compare investment and expected benefit beforehand via /en/costs/rpa-roi.