AI / Generative AI Automation for Business

Generative AI

We use generative models where they can reduce time and produce verifiable results.

Background

When this service makes sense

Functionalities for generation, summary, classification or assistance in repetitive processes.

  • Main needGeneral AI for business
  • Role in the projectAI agents, document processing and automation connected to real processes, with rules, logbooks and human verification.
  • Result pursuedWe use generative models where they can reduce time and produce verifiable results.

Deliverables

What usually comes into the project

The exact list shall be adjusted after the audit, but these modules frequently appear in the generative projects of the type.

01Usage cases
02Controlled promotions
03Output templates
04Validation
05Cost limits

Connection

Service works better when it's connected to the rest of the project

Any service works better when connected to the rest of the ecosystem: content, SEO, data, operation, hosting and maintenance.

  • AI agents
  • Document processing
  • Sales automation
  • Integration with AI platforms

Frequently Asked Questions

Before we begin the project

Choice, stages and support for Generative AI.

01 / Choice

What's useful to know

Generative AI can cause mistakes?

Yes. That is why we include checks, limits and flows with approval for important data or actions.

What information are we preparing for the first discussion?

Examples of requests or documents, process steps and approved sources. We clarify what data can be used, who validates the result and what actions require approval.

02 / Planning

Purpose, budget and stages

What can the project include?

For Generative AI, starting points are: Usage cases; Controlled Prompts; Output templates; Validations; Cost limits. In the offer we specify deliverables, limits and responsibilities; the list adapts to your situation.

How do we set the budget and the timetable?

We separate data preparation and integration from the cost of use. The volume, models, external services and the level of human verification influence the estimation; we start with a limited and measurable flow.

03 / Continuity

Verification and support

How do you verify the result before handover?

We use representative examples, including difficult cases, and compare results with validated answers or rules. We track errors, costs and required interventions: a fluent response is not proof of accuracy.

What happens after handover?

Updates of sources, adjustments of rules and reassessments of results may be required after launch. We set cost monitoring, usage limits and escalation to a person for sensitive situations.