Low-code is a way to develop applications quickly using drag-and-drop models and minimal coding. You can develop applications quickly and easily by connecting ready-made components through a visual interface.

Low-code is suitable for web and mobile applications such as customer portals, process automation, modernising legacy systems, and process-supporting apps. In our practice, we work on both smaller initiatives and business-critical applications.

Low-code helps organisations develop and launch new solutions or business models quickly, so they can respond better to changing market demand. This enables innovation, optimisation, and automation without disrupting existing systems, keeping day-to-day operations stable. Ideas from the business are turned into concrete applications faster, with less dependence on scarce IT departments. This makes the organisation more agile, more efficient, and better prepared for the future.

The Clean Core principle is about keeping the standard core of an ERP system as intact as possible. Where specific business needs require additional functionality, this is realised outside the core. The starting point is not that customisation disappears, but that it is set up in a thoughtful way, so the stability and future-proofing of the ERP landscape are maintained.

Agentic AI is suitable for use cases where, alongside content generation (generative AI), you also want action. For example, executing tasks, planning steps, supporting decisions, and optimising processes within workflows. Think end-to-end process orchestration, dynamic case handling, and integrating actions across systems.

Agentic AI goes a step beyond generative AI: You build agents that are given goals and can then (within boundaries) reason, plan, and carry out actions. Mendix focuses explicitly on quickly developing, deploying, and scaling AI agents and (multi-)agent applications.

Mendix brings orchestration together in one platform layer across people, systems, and agents. This makes automation more adaptive, and you can design, run, and optimise processes more intelligently with AI. It also helps create AI readiness. Agents work better when data and processes are not fragmented.