AI + Simulation
Build machine learning and generative AI models your business can actually explain — with a visual no-code canvas for domain experts and a full Python/R environment for data scientists. MXTechies designs, trains, and deploys AI Studio (RapidMiner) models on Mendix, for enterprises around the world.
What it is
Quick answer
AI Studio (RapidMiner) is an enterprise AI and machine learning platform, part of the RapidMiner portfolio within Siemens Xcelerator, that lets both business users and data scientists build, explain, and deploy AI, ML, and generative AI models. It connects to cloud, on-premises, and IoT data sources and can run in the cloud, on-premises, or hybrid to meet regional data residency needs. MXTechies scopes the use case, builds the model in AI Studio, and delivers it through a Mendix application for enterprise teams to use.
Explainability & governance
A prediction nobody can account for is a prediction nobody will act on. Three things make the difference between a model that gets used and one that stalls in review.
01 — Transparency
Models and predictions stay auditable, with a visible process for how each output was reached — which matters for internal trust and for the compliance expectations regulated industries such as financial services and pharma already work under, wherever they operate.
02 — Control
User authentication, access authorization, and data encryption and audit trails are built into the platform, so every insight can be traced back to a controlled, permissioned source rather than an open dataset.
03 — Both audiences
Data scientists can build in a full Python and R environment, or use the visual drag-and-drop canvas, and combine both approaches inside the same workflow — so a team isn’t forced to standardize on one skill level.
What it delivers
To the data you already have. Cloud platforms, data lakes, warehouses, SQL databases, flat files and IoT streams connect directly, so models train against live, governed data instead of one-off exports.
And deploys models quickly. Domain experts build through the visual canvas; data scientists build complex models and blend Python or R with the platform’s own workflow components.
From workgroup to enterprise. The same models reach one team or the whole organisation without compromising security, on any major cloud, on-premises, or hybrid.
How we deliver
A model in a workbench doesn’t move a business forward until people can use it. MXTechies scopes the use case, builds and validates the model in AI Studio, and delivers it through the Mendix application layer your teams already work in — with delivery teams spanning the United States, UAE and India, covering business hours across regions.
start with the outcome
We identify the highest-value prediction, classification, or generative task for the business — the one with clear data availability and a measurable outcome — rather than starting with the platform’s full feature list.
where the real work hides
Source systems are connected in place, and data is profiled and prepared inside AI Studio’s workflow so the model is trained on governed, traceable inputs.
no-code, code, or both
Models are built using the no-code canvas, custom Python/R, or a blend of both, then validated against business-defined accuracy and explainability criteria before deployment.
where people actually work
The validated model is deployed through a Mendix application — dashboards, workflows, or an embedded AI feature — with role-based access and ongoing monitoring configured before go-live.
Where it pays off
Why MXTechies
Mendix Certified Partner and Siemens Xcelerator partner, building production AI applications on Mendix.
Building and validating models, then delivering them through the Mendix application layer.
Across manufacturing, financial services, pharma, and other regulated industries.
Typical production delivery cadence, from a scoped engagement to an application people use.
Delivery teams span the United States, UAE and India, covering business hours across major global regions.
Start here
Talk to our team about scoping an AI Studio pilot — on your data, deployed on Mendix, delivered by a team spanning the United States, UAE and India.
What to bring
The conversation
What you leave with
“If the honest answer is that you don’t have the data yet, we’ll tell you that — and what to fix first.”
Or read more about our work across the Siemens ecosystem.
FAQ
AI Studio is the machine learning and AutoML product within the RapidMiner portfolio, part of Siemens Xcelerator. It lets business users and data scientists build, explain, and deploy AI and machine learning models through a visual drag-and-drop canvas or a code-based notebook environment.
No. AI Studio is built for both audiences: domain experts can build effective models through a no-code visual canvas, while data scientists can work in a full Python and R development environment and combine both approaches in the same workflow.
Every model built in AI Studio is designed to be auditable, with a visible workflow showing how each input was transformed and how each prediction was reached, so decisions can be traced back to source data instead of treated as a black box.
Yes. AI Studio connects to cloud data platforms, on-premises databases, data lakes, warehouses, flat files, and IoT data streams, and can be deployed on any major cloud, on-premises, or in a hybrid model to fit data residency requirements.
AI Studio focuses on building and deploying machine learning and generative AI models. Graph Studio focuses on connecting enterprise data into a knowledge graph. The two are complementary: a knowledge graph can supply the grounded context that makes AI Studio’s models more accurate.
MXTechies scopes the use case, builds and validates the model in AI Studio, and delivers it through a Mendix application layer, with delivery teams in the United States, UAE and India aligned to each market’s data governance requirements.