Intelligent Automation & AI
Bring AI into governed operations on the Mendix platform: an enterprise context layer, business-tuned models and forecasting, human-agent collaboration, and traceable on-prem or cloud deployment.
According to Mendix (Siemens), most AI models never leave the lab — governance is the last barrier before production. Mobino’s Intelligent Automation & AI service implements the Mendix platform’s AI Studio and Graph Studio capabilities to bring agents into real operations with governance built in from the start.
Before data reaches an AI system, we build a context layer — a knowledge graph that connects data from your warehouses, data lakes and documents without moving or replacing the source data, with role-based access and auditable transformations at the graph layer.
On top of that context layer, we develop models tuned to your business — from low-code for domain experts to code-first for data scientists — with automated training and forecasting, and continuous drift monitoring once a model is in operation.
Agents are orchestrated with clearly defined roles, working alongside people rather than replacing them outright, with every action logged and traceable. The platform supports cloud, on-premise or hybrid deployment to fit each industry’s security requirements.
AI in real operations, governed end to end
Context layer
A knowledge graph connecting data from multiple sources without moving or replacing the source data.
Models & forecasting
Automated training and forecasting tuned to your business, with continuous drift monitoring.
Agent orchestration
Agents work alongside people with clearly defined roles, not as a full replacement for human decisions.
Governance & deployment
Every action is traceable, with flexible cloud, on-premise or hybrid deployment.
Why you need a context layer before AI
As Mendix puts it, data isn’t what AI agents are missing — context is. A knowledge graph connects your existing data into one shared context layer for every agent, model and application.
No rigid schema required
Ingests data from warehouses, data lakes and documents without pre-standardising the schema.
Governance at the graph layer
Role-based access and auditable transformations and inference before data reaches any application.
Lower inference cost
Fewer inference rounds and lower token cost, with AI output traceable back to its source data.
The problem is not your AI model, it is how the enterprise operates around it
Most enterprises layer AI on an operating model that was never designed for it. Mobino helps close the three architectural gaps that separate leaders from the rest.
Enterprise context at machine scale
The gap: data without meaning, AI that cannot reason across disconnected systems. We build a live context map of your enterprise so people and agents share one reality.
Unified execution, from intelligence to action
The gap: recommendations stop at the dashboard and value leaks in manual handoffs. We orchestrate data, models, agents and workflows so recommendations become accountable actions.
Governance embedded at every level
The gap: shadow AI, black-box execution, pilots that never pass audit. We enforce policy at creation so every action is traceable and every decision auditable.
Five layers of an autonomous operations platform
Nothing gets ripped out. ERP, CRM, OT, supply chain and finance remain the sources of truth; the five layers below make them smarter, faster and governed.
Knowledge Graph — shared context
A live map of how systems relate, continuously updated.
AI/ML Modelling — business-specific intelligence
Models trained on your operations, history and decisions.
Agentic Development — build the hybrid workforce
Agents run where appropriate, people step in at the right moment, business and IT in one environment.
Process Orchestration — connect across the enterprise
A signal in operations triggers action in finance, in one traceable process.
Enterprise Trust Layer — governance around it all
Clear guardrails, end-to-end traceability, security and compliance from creation.
Ready to bring governed AI into your operations?
Start with one painful process that already has data and a measurable goal.
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