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We automate the work nobody should be doing by hand

We connect systems, documents and data into a process that runs without retyping, chasing deadlines or copying information between screens. We add AI where it genuinely saves work, not where it just sounds good.

Code displayed on a monitor

What to automate first

We don't start by asking about AI models. We look for a process that is frequent, repetitive and measurable.

If you recognise two or three of these signs, a free online consultation will show whether to start, and where.

  • The same information is retyped between email, spreadsheets, CRM and the ERP system.
  • Someone copies invoices, orders or contracts from PDFs into your software every day.
  • A report is pieced together by hand from several files every week.
  • Deadlines are tracked in personal calendars and messages.
  • Company knowledge exists in documents, but it's quicker to ask a colleague than to find it.
  • Two systems in the business don't talk to each other, so someone does it for them.

What we do, from process to a working workflow.

  1. 1

    Process mapping

    We map out triggers, inputs, decisions, exceptions and responsibilities before the first automation is built.

  2. 2

    Automation sprint

    One process end to end: design, workflow in n8n, Make or Power Automate, error handling, notifications, testing and documentation. Usually one to three weeks.

  3. 3

    System integration

    Connecting two systems via API: data flow and validation, handling of duplicates and conflicts, retries after errors and a view of the sync status.

  4. 4

    AI document extraction

    Extracting data from invoices, orders and contracts, classification and summaries. Documents the model isn't sure about are passed to a person.

  5. 5

    Company knowledge assistant

    Search and answers based on approved documents, with a link to the source and an answer accuracy test before go-live.

  6. 6

    Monitoring and costs

    Every run leaves a log, every error triggers an alert, and with AI we also keep an eye on the cost of model queries.

What you get in writing.

The solution must remain maintainable after the project ends.

  • Process map

    Before and after, with exceptions and the person responsible for each step.

  • Workflow documentation

    Systems, access, dependencies and error handling, written up so someone else can take it over.

  • Test scenarios

    Valid, invalid and edge cases used for acceptance.

  • Guide and training

    What to check and how to respond when a process stops. Plus short training for the people who use it.

Who is responsible for what.

We agree who is responsible for what before quoting. Every project has an owner on your side.

On the NexaIT side

  • analysis of the process and dependencies between systems
  • solution design with acceptance criteria agreed before starting
  • building, testing and documenting the workflows
  • AI model selection and accuracy testing where AI is part of the process
  • bug fixes for 30 days after acceptance

On your side

  • naming the process owner and the decision-maker
  • access to systems and sample data for testing
  • users taking part in acceptance testing
  • tool accounts and licences, and AI model usage costs, paid directly to the provider
  • deciding what the automation may do on its own and what needs approval

What this service doesn't include.

Clear scope boundaries are part of a good contract. We talk about them before you sign, not when the first invoice arrives.

If a simpler organisational change would solve the problem better than automation, we'll tell you before quoting.

  • automating a process nobody in the business can describe
  • legal or financial decisions made by AI without human approval
  • deployments on employees' personal accounts or undocumented access
  • AI model usage and tool licences, which you pay directly to the provider
  • developing features in a third-party system whose vendor doesn't provide an API

When a project makes sense, and when it doesn't

It makes sense if

  • The process happens at least several times a week.
  • You can measure the time taken or the number of errors before and after the change.
  • There is someone who will own the process and be responsible for it.

We don't recommend it if

  • The process changes every few days and nobody knows what it should look like.
  • The goal is just "having AI", with no problem to solve.
  • There's no access to the systems that need to talk to each other.

What affects the price

We price the scope, not the number of buzzwords. As a guide: an automation sprint for one process from PLN 7,000 net, integrating two systems from PLN 7,500 net, AI-powered automation from PLN 9,000 net.

  1. the number of systems to connect and the quality of their APIs
  2. the number of exceptions and decisions in the process
  3. whether AI is part of the process and what accuracy is required
  4. the required level of monitoring and error handling
  5. the amount of historical data to migrate
View packages and rates

Questions before you decide.

Does automation require replacing current systems?

Usually not. First we check what can be connected using the tools you already have. We only suggest replacing a system if there is no way to access it from outside.

Does our data have to go to an external AI model?

Not always. The architecture depends on data confidentiality, legal requirements and budget. With sensitive data, we agree in writing what may and may not leave the business before we build anything.

What happens if an automation stops working?

You get a notification, and every run leaves a log, so you can see at which step and why the process stopped. The guide tells you what to do straight away. We can take on ongoing maintenance as part of managed support.

What does AI cost to run after implementation?

Model queries are a recurring cost that depends on the number of documents and questions. We estimate it before starting, show it separately in the quote and monitor it after go-live.

Related

Free · 60 minutes online · no obligation

First, a conversation about the process, then the tool.

  1. You tell us about the processOnline, by video call. What takes up time today, which systems hold the data and what you want to achieve.
  2. We tell you whether it's worth itSometimes a change to a spreadsheet or a process is enough. If so, we'll say that instead of proposing a project.
  3. You get the next stepBy email after the meeting: what to map, what data to prepare and what the price depends on.

We don't use a contact form. We answer the phone and reply to emails.