SmartNeura

Activate your agentic enterprise: built on the Mendix low-code platform.

Autonomous Enterprises with Agentic AI

Agentic AI is not a better chatbot. It is software that can plan, reason, and execute work inside real processes. We build that on Mendix (the enterprise low-code platform for a hybrid workforce of people and agents) so context, governance, and control are present on day one, not bolted on after a viral demo.

Scale engine

  • Load1× → 10×
  • AgentsRunning
  • OversightHuman

The practice

What this engagement changes.

Four working layers: the foundation we put in place so the rest of the program can run.

  1. 01

    Agentic development

    Production-grade agents with Mendix Maia: visual models anyone can inspect, built from your organization’s real context, not a pile of generated code no one owns.

  2. 02

    Process orchestration

    One governed layer for business events, AI signals, and human decisions, so agents, systems, and people stay in a single accountable flow.

  3. 03

    Enterprise context and knowledge

    Knowledge bases, RAG, and semantic search so agents answer and act on your data, in something close to real time.

  4. 04

    Enterprise governance

    Auditable, traceable, policy-enforced AI. Human-in-the-loop is structural: the process cannot skip it when it matters.

01

From pilot to production

  1. 01

    Maia Plan: workshop notes and briefs become execution-ready delivery plans in hours, not a six-week documentation cycle.

  2. 02

    Maia Make: conversational generation of data models, pages, and process logic that remain visual and reviewable.

  3. 03

    GenAI connectors: OpenAI GPT on Azure, models on Amazon Bedrock, or the stack your security team will approve.

  4. 04

    Machine Learning Kit: custom models inside apps when latency and data residency will not tolerate a round-trip to a public API.

02

Where agentic AI earns its keep

  1. 01

    Autonomous service desks and IT operations (AIOps) with a clear escalation path.

  2. 02

    Self-healing networks and predictive assurance.

  3. 03

    Intelligent document and knowledge processing.

  4. 04

    Customer journeys orchestrated by agents, with humans on the exceptions that need judgment.

03

Control and cost

  1. 01

    Prompt management so system behavior can be tested, versioned, and explained.

  2. 02

    Token and usage monitoring so GenAI cost is compared to the value it creates.

  3. 03

    Function calling (ReAct) so agents can act across systems, not only talk about them.

  4. 04

    Open, MCP-ready architecture: no requirement to lock the estate to a single model vendor.

Does this practice match the year you are in?

Book an online consultation. We will return with a clear reading of your current state, the constraints that matter, and a path that fits how your organization actually operates.

Book a consultation