IT teams spend most of their day on repeat work: password resets, access requests, alert noise, patching and audit evidence. Agentic AI for IT services changes that. Our AI agents pick up the request, check your systems, take the approved action and close the loop, while your engineers focus on work that needs them.
MXTechies builds, governs and runs IT agents on the Mendix platform, connected to the service desk, cloud, security and development tools you already use.
An AI agent uses a large language model to understand a request, plan the steps, call tools and APIs to act, and check the result. Unlike a chatbot, it does the work. Unlike a script or RPA bot, it copes when the request or situation changes, within limits you set. That suits IT, where most work follows known steps but every case is slightly different.
Tells the user what to do next, but a person still does the work.
Fast on the happy path, but breaks when the request or situation changes.
Understands, plans, acts through tools and APIs and checks the result, within limits you set.
We review your ticket and alert data to find the highest-volume, lowest-risk work to automate.
One agent runs on real tickets or alerts, with a baseline and target agreed up front.
We connect the agent to your ITSM, monitoring, cloud and identity tools through APIs.
Permissions, human approval for risky actions, audit logs and cost limits go live with the agent.
We monitor accuracy and cost per task, and add new tasks as trust grows.
Here is one common IT request handled end to end by an agent:
No one retypes a form or chases an approval, and every step is logged for audit.
An employee writes in Microsoft Teams: “I need access to the finance dashboard.”
The agent checks the employee’s identity, role and the access policy in your ITSM tool.
If the role qualifies, it raises the ticket and asks the manager to approve in one click.
Once approved, it grants access in your identity system, confirms with the employee and closes the ticket.
If anything does not match policy, it passes the case to the service desk with all the details attached.
We agree the metrics before we build and report against them after go-live:
Share of tickets or alerts resolved without a person
Mean time to resolve (MTTR) and first-contact resolution
Engineer hours returned to project work
Cost per ticket, including model and review costs
Mendix 11 added an Agents Kit, Model Context Protocol (MCP) support, AI guardrails and workflows that call agents as a step. That gives IT agents approval screens, integrations and security out of the box, and a choice of models from providers such as OpenAI, Amazon Bedrock, Google Gemini, Mistral and Anthropic Claude.
Work with a dedicated team that understands US business needs and delivers scalable enterprise IT solutions with global technology expertise.
Work with a dedicated team in India that understands local business needs and delivers scalable enterprise IT solutions with global delivery expertise.
Work with a team that understands the UAE business landscape and delivers enterprise IT solutions tailored to local needs, backed by global technology expertise.
Share a month of ticket or alert data and we will show you which tasks an agent could take on first.