Artificial intelligence in businesses

AI starts with a clear problem.

Assess applications, test a pilot and integrate what makes sense into the company's daily work. With quality criteria, care for data and human oversight.

Talk about a project. Understand the approach.
Illustrative process

With human supervision.

Starting points

Where to investigate.

These are possibilities to assess, not ready-made solutions or guaranteed results. Each application depends on the data, processes and risks involved.

  1. Scattered information

    Assess support for consulting documents and preparing summaries, considering sources, permissions and review of responses.

  2. Repetitive tasks

    Investigate steps for classifying, organizing or preparing information that could receive AI assistance.

  3. Software engineering

    Assess support for analysis, documentation, development and review, with project context and technical validation.

Process

Test before expanding.

  1. Assessment

    Choose a problem with a defined scope and understand inputs, outputs, users and constraints. Define how to evaluate the proposal.

  2. Pilot

    Test a limited scope with representative examples and authorized data. Record successes, errors, review effort and limitations.

  3. Integration

    If the pilot justifies moving forward, design the connection to systems, permissions, failure handling and operation.

  4. Adoption

    Guide the people involved, monitor use and review behaviour before expanding the scope.

Criteria

What needs to be clear.

  1. What AI does

    Task, context and limits defined for the proposed use.

  2. Who checks

    Those responsible for review and for deciding whether to use each output.

  3. What data goes in

    Authorized information, required access and terms of use for the tools.

  4. How to evaluate

    Examples, quality criteria and costs to observe during the pilot.

Applied experience

AI within engineering work.

At NASAH, we assess the use of agents in planning, architecture, development and review, with context for each repository and human approval. Our approach is to test, check and adjust before expanding use.

Getting started

Frequently asked questions.

Is it necessary to develop a custom model?

That depends on the problem. The assessment should consider existing tools, integration, data, costs and limitations before choosing a solution.

Does the pilot guarantee savings or productivity?

No. The pilot is used to evaluate the application against defined criteria. Any gain needs to be measured in the context where it will be used.

Can AI act without review?

The level of review depends on the task and its risks. The approach starts with human oversight and explicit limits on actions.

Contact

Which problem deserves a pilot?

Tell us how the task works today, who is involved and what you would like to evaluate with AI.