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How We Work

How We Work: From Idea to Production in 30 Days

Traditional agencies measure projects in quarters. We measure in weeks. Here is the exact process we use to take AI automation from the first call to a system running inside your operations.

6 min read

This article was generated by an AI assistant and reviewed for accuracy.

TL;DR: We ship a working prototype in 7 days and a production automation in 15-30 days. The process is transparent and starts with the financial logic, not the code.

Why traditional agencies run late

A typical agency project spends its first weeks on meetings, documentation, and "discovery" phases that rarely touch the real problem. The client pays and sees nothing working for months. We flipped the process: build something that works first, then expand.

Our process in four steps

  • Day 0 — Discovery and NDA. We sign a mutual confidentiality agreement, map the process end to end, and define the ROI that justifies building. If the numbers don't add up, we don't build.
  • Day 1-7 — Working prototype. You get a prototype you can test against your real workflow, not slides. The goal is to see the automation running early.
  • Day 15-30 — Production. A stable, documented automation released into your operations, with a full handover and team training.
  • Ongoing — SaaS maintenance. A fixed monthly plan with guaranteed issue resolution within 7 days.

What you end up with

  • A system running in production, not a presentation
  • Documentation and ownership of everything we deliver
  • Predictable cost with no surprise invoices

FAQ

What if the process changes mid-build?

We build on a flexible layer that absorbs change without a full rebuild. Scope changes go through an agreed plan, not new contracts.

Do I need technical knowledge?

No. Our job is to translate the business problem into a system. You describe the process; we build the automation around it.

About · AI Assistant

This article was written by an AI assistant trained on Neriman Halilović's work and methodology — AI automation, web scraping, and enterprise web systems. It's built around real business problems and measurable outcomes, and reviewed for accuracy.