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AI process automation

AI agents and intelligent workflows that cut repetitive work, with human oversight and data under control.

Less manual work

Email, documents, tickets, reports and system updates - the repetitive work goes to AI, the team does work that carries value.

Human oversight

Every automation includes validation, review and traceability - AI speeds things up, people decide.

Integrated with your systems

The automation talks to the CRM, business systems, email and archives you already use, without upending your tools.

Repetitive work does not deserve your people

Many business activities no longer need manual steps: gathering information, classifying email, filling in documents, summarising meetings, analysing tickets, updating the CRM, generating reports, checking deadlines, searching documents. These are hours every day — and they are exactly what AI agents do best.

Xion designs automation based on AI and custom software that helps a team work faster without losing human oversight: every flow is built with access control, traceability, validation and attention to data protection.

Examples of the automation we build

Our principle

AI has to speed up the work, not replace the control. So every automation includes points of human verification on the critical steps, permissions differentiated by user and department, and complete logs of what the AI did and why.

From process to automation, with one partner

Automation lives inside your infrastructure: servers, cloud, access, backup. Xion designs it, integrates it and maintains it — alongside security and custom software where the process needs a dedicated application. Start from the AI Readiness Assessment to identify the first process worth automating.

Conventional automation and AI: when to use which

Not everything needs artificial intelligence. A flow with fixed rules and structured input — moving a file, sending a notification when a status changes, synchronising two databases — is better solved with conventional automation: simpler, more predictable, cheaper. AI comes into play when the input is unstructured: an email written in a thousand different ways, a document to be understood, a request to be interpreted, a text to be summarised. That is where classic automation gives up and AI opens new possibilities. In designing a solution we choose the right instrument for each step — often the two worlds coexist in the same flow.

A typical project, from idea to result

Take a frequent case: handling incoming email on a shared mailbox. Today somebody reads them one by one, works out what each is about, routes it to the right department, sometimes replies. With AI automation: the emails are classified automatically by type and urgency, the relevant data is extracted and entered into the business system, recurring requests receive a draft reply ready for human review, and the complex cases are flagged to a person. The result is not “less work for the computer”: it is more time for people on the things that genuinely need judgement, and faster response times for the client.

The non-negotiable principle: the person decides

Automation that acts without oversight is a risk, not an advantage. So every flow we design includes points of human verification on the critical steps — a payment, a reply to an important client, a decision with consequences — while AI handles the repetitive, low-risk part. We add complete traceability (who did what, and why), differentiated permissions, and the ability to correct and improve the behaviour over time. The right automation is the one you trust because you control it.

Frequently asked questions

Which processes can be automated with AI agents?

Classifying email and tickets, extracting data from PDFs, invoices and contracts, generating drafts and reports, updating CRM and business systems, approval workflows, searching company documents and answering from internal knowledge bases.

What is the difference between conventional automation and AI automation?

Conventional automation follows fixed rules and breaks as soon as the case changes. AI handles unstructured input - text, documents, emails written in a thousand different ways - and therefore covers processes that were previously impossible to automate.

How do you ensure AI does not make mistakes with the data?

With flows designed around human oversight - AI proposes, a person validates the critical steps. We add differentiated permissions, an audit trail and quality checks on the outputs before they touch your systems.

How long does the first automation take?

For a well-bounded process, generally a few weeks from analysis to release - we always start from the flow with the best benefit-to-effort ratio identified in the assessment.

Tell us about the process you do by hand today

The projects that work start from one precise, repetitive activity rather than from a list of features. Describe it and we will tell you whether automating it is worth it.