Understanding your business and data

We help you understand what AI can (and can't) do in your specific context.

What does the initial consultation include?

• Identifying opportunities

  Together, we'll uncover where AI can bring the greatest value.
• Assessing available data

  We review the quality, structure, and volume of the data needed for AI solutions.
• Technical feasibility

  We assess whether AI is a good fit for your case – and what it would involve.
• Recommended next steps

  We outline a path toward a prototype or final solution.

AI system design and integration

We design the architecture, choose the right tools, and define how AI will work in your daily operations.

What can the solution design include?

• Technology and integration plan

  We describe how the chosen AI tools will be integrated into your system – including data flows, API connections, and system architecture.
• Secure and sustainable solution

  We take into account data protection, auditability, responsible AI use, and realistic operating costs.

AI project delivery

We implement proven tools and models – for automation, internal assistants, or data processing.

What can we deliver?

• AI tool integration

  We connect tools like OpenAI, Claude, or Mistral to your system via APIs.
• Automation and assistants

  We deploy AI for specific tasks – from sorting requests and summarizing content to basic customer support.

Validating and fine-tuning outputs

We test how the model performs in practice – adjusting accuracy, speed, and reliability.

What do we test?

• Accuracy, performance, and robustness

  We check the quality of outputs, response times, and how well the model handles errors and bias.
• Safety and real-world behavior

  We test how the model reacts in different scenarios and prepare it for live operation.

AI as part of your business

We support you in launching to production and maintaining long-term performance.

How does deployment and support work?

• Production deployment

  We transition the solution into your live environment and test it thoroughly.
• Training and documentation

  We transfer know-how to your team, including documentation and best practices.
• Performance monitoring

  We continuously track how the system behaves and report the results.
• Iterating and improving

  We refine the model based on feedback and updated data.