Artificial Intelligence for businesses in Madrid

On-premise enterprise AI for small and mid-sized businesses in the Madrid region. The model runs on your own infrastructure: documents never leave the company.

What Polaris AI does

Polaris AI installs an agentic AI platform inside the company: a physical machine or a private virtual machine, on your own network, where the models run. On that base, the system reads what comes in — email, invoices, delivery notes, photos of receipts, documents dropped into a folder — classifies it, files it with its date, and leaves ready the work that used to be done by hand.

The difference from a cloud AI tool is not the capability of the model: it is where the documents are processed. In a cloud solution, the content travels to a provider’s servers. In an on-premise installation, it does not leave the company network. For a law firm handling case files, a clinic with medical records, or an accounting firm holding its clients’ payroll, that difference is what decides whether the project is viable at all.

No action runs on its own: Polaris proposes and a person approves. Human approval is a step in the process, not a setting you configure.

Which Madrid businesses can make use of it

It does not depend on the industry, but on three things: how much paperwork moves through the business, how much of the information is confidential, and how much time goes into repetitive tasks.

• Businesses under a duty of confidentiality

  Law firms, accounting and tax firms, advisory firms, clinics, and medical centers. When professional secrecy or Article 9 of the GDPR is involved, uploading documentation to an external provider stops being a technical decision and becomes a legal risk.

• Businesses with a high volume of incoming documents

  Distribution, logistics, wholesale, construction. Hundreds or thousands of invoices, delivery notes, and orders a month that someone has to open, read, file, and search for again when the quarter closes.

• Small and mid-sized businesses, 5 to 50 employees

  The size at which administrative work already weighs but there is still no IT department. Exactly where a tool that needs configuring and maintaining every day does not hold up, and one that works on its own does.

• Businesses that already have their software and do not want to change it

  Polaris sits on top of what you already use rather than replacing it. Today it leaves the work ready in Excel, CSV, or PDF; writing directly into management software such as A3, Sage, or Odoo is on the roadmap.

Which processes can be automated

These are the processes running in production today. What is built but not yet connected, and what is still in development, is kept separate and visible in the product status section.

• Document classification and filing

  Business email is checked automatically several times a day. Invoices and delivery notes are recognized with their supplier, number, and date. A photo of a receipt is classified on its own, and so is whatever is dropped into a folder on a computer. Duplicates are detected.

• Preparing the handoff to your accountant

  Because everything is classified and dated from the moment it comes in, the quarter goes out filtered and exported to Excel, CSV, or PDF without searching for anything again.

• Plain-language questions about your own documents

  Asking "which supplier invoices are unpaid?" and getting an answer from what is in the archive, from the desktop or over WhatsApp, without learning where everything lives.

• Notifications and approvals

  When something new comes in, Polaris notifies you on the desktop and waits. If nobody answers, the notice reaches you on WhatsApp. Approving or rejecting is one click.

What on-premise means and how the data is protected

"On-premise" means the software and the models run on hardware inside the company network: a server in the office or a private virtual machine. There is no external service processing the content of the documents.

In a Polaris AI installation, the container network where the models run has no internet access. The only outbound connections are to the services the company already uses — its own Google Workspace and its own WhatsApp — and they are auditable: outbound traffic can be reviewed and verified.

That changes the GDPR conversation. There is no transfer of data to a third party that needs covering by a data processing agreement, because no third party receives the content. For special categories of data — health data at a clinic, for instance — and for professional secrecy, it is the difference between being able to use AI and not.

What infrastructure it takes

It depends on the size of the company and how many processes are to be automated: a three-person office with dozens of documents a month is not the same as a distributor with thousands. The specific hardware is chosen after the assessment, once the real volume is known.

Polaris AI guides you through choosing and purchasing the server and, depending on the case, can supply it as a turnkey solution. Setup is carried out by a certified integration partner at your premises, and training is tailored to your team and your schedule.

You do not need an IT department of your own. You do need one person inside the company who knows how the work is done: who opens the email, where things are kept, and what happens when an invoice arrives. That knowledge is what makes the deployment worth anything.

How a project starts

The first step is the Polaris AI Assessment: a 30-minute meeting where we look at how you work — which tasks repeat, what comes through email, WhatsApp, or Excel, which tools you have, and which processes are still manual — and afterwards we send you a document with what we found and where we would start. It is carried out by a person, not generated automatically.

Before that, the savings calculator on the home page gives a first estimate using your own numbers: how many people handle paperwork, how many hours a week, and what that hour costs. It is an estimate, not a promise: it tells you whether the conversation is worth having.

If the assessment finds something worthwhile, the next step is a demo on a case similar to yours, and then the deployment proposal.

Read on

The concepts on this page, explained one by one:

• What is on-premise AI? The definition, how it works, and when it makes sense.
• On-premise AI versus cloud AI The real differences in architecture, control, and cost.
• What is RAG and what is it for in a business? How an AI answers using a company’s own documents.
• AI and GDPR: what changes when the model is local Transfers, data processors, and special categories.
• AI for accounting and tax firms Invoices, deadlines, and professional secrecy.
• AI for clinics and medical centers Records and health data that never leave the clinic.
• AI for law firms Case files and contracts indexed on-premise.
• AI for logistics and distribution Delivery notes, orders, and stock.