Your people already use AI, often on personal accounts. We help you pick the right tool, roll it out with company accounts, connect it to your documents and write rules your team actually follows.
Using ChatGPT properly at work means adopting a business plan (ChatGPT Business or Enterprise, Claude Team or Enterprise, Gemini in Google Workspace, Microsoft 365 Copilot) with company-managed accounts and verified data settings, plus a usage policy and the training the EU AI Act calls for. UreTech compares the plans for your case, sets up access and connectors, integrates the tools with your systems and trains your people, while you buy the licences directly from the vendor or your usual supplier.
The situation we find most often in SMEs.
Everyone uses their own free version. The company does not know what data went in and cannot revoke access when someone leaves.
Contracts, quotes and personal data end up in tools whose privacy settings were designed for consumers.
Those who write good prompts get a lot out of it; the others give up. Nobody shares what works.
The EU AI Act has required AI literacy measures since 2 February 2025, and Italian Law 132/2025 adds rules for some professions.
The right question is not which model is best overall, because the ranking changes every few months. What matters is where your people already work and which data they need.
Makes sense if the company lives in Outlook, Teams, Word, Excel and SharePoint. It works on the documents each user can already open, so SharePoint and OneDrive permissions must be cleaned up first: a file shared with everyone by mistake becomes an answer for everyone.
The natural choice for companies on Gmail, Drive and Meet. Here too, order in shared folders comes before AI.
The most widespread, and the one people already know from personal use, with connectors to Google Drive, SharePoint and other services. Good as a general assistant and for building assistants dedicated to one department.
Strong on long documents, analysis and technical writing, and it connects to other tools through the MCP protocol. A good alternative or companion for legal, technical and admin teams.
Many companies end up with two tools: the office-suite one for everyone and a specialist one for a department. Per-user prices, usage limits and data terms change often: we check them on the official price lists on the day we prepare the proposal. If data cannot leave the company, the route is a private on-premises model.
You can ask for the whole journey or just one part.
Plans compared on your use cases, number of users and data, with annual list costs.
Verified domain, single sign-on where the plan supports it, admin roles, settings on data retention and use.
Connectors to Drive, SharePoint or company folders with the right permissions. We fix wrong sharing first.
Custom assistants and API or MCP links to ERP, CRM and databases when live data is needed.
Written rules: which tools, which data is allowed, who checks results, what to tell customers.
Hands-on sessions on each department’s real tasks, with prompt examples and pitfalls.
The main vendors’ business plans state that customer business data is not used to train their models unless the company opts in. Turning on the right plan is not enough, though:
For each point you get a sheet citing the vendor’s official source and the date we checked it. For legal assessments we work with your DPO or privacy adviser.
An example of how we handle sensitive data: the assistant on our own website runs on an open-weight model on one of our servers rather than an outside service. It is the same approach we propose when ChatGPT or Copilot are not enough.
After rollout, the step that pays off most is almost always a dedicated assistant: a custom GPT, a Claude project or a Copilot agent with the instructions, documents and tone of one department. Engineering loads manuals and product sheets, customer service the approved standard answers, accounts the internal procedures.
We build them with the people who will use them, test them on real questions and agree who updates them when documents change. When an assistant needs data that changes daily, such as orders or stock, we connect it to your systems with a custom AI agent.
A few weeks, without stopping work.
Who already uses AI, for what, with which data. Thirty minutes is enough to see where to start.
Recommended tool, list licence costs, setup work and training schedule.
Accounts, access, connectors, data settings and a pilot group.
Written rules and sessions by department, then rollout to everyone.
Who uses it and for what, where a dedicated assistant or integration is needed.
Technology ecosystem
We build with the main vendors’ models and with open models installed on-premises, choosing case by case.
AI agents and automations built with the models and tools that fit the case: in the cloud when it makes sense, on-premise when data must stay inside the company.
Custom AI agentsProcess automationPrivate LLM on-premiseAI consulting
The other pieces of AI at work.
Hands-on courses by department and AI Act literacy.
When data cannot leave the company.
Where AI really pays off, before you spend.
Starting prices and running costs.
When you need an agent connected to your systems.
Tell us how many people are involved and which tools you already use. We reply within one working day.
We will email you within one working day to book the 30 minutes. If it is urgent, message us on WhatsApp.
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Mon–Fri 9:00–12:30 and 14:00–20:00 (CET).