An international testing and certification group set out to generate quotes for company certifications automatically. The solution went into production in 2018 – with a human in the loop and a weekly C-level steering committee.
quotes for company certifications were produced by hand. Every quote required experience with standards, audit scope and effort estimation – knowledge held by experienced specialists that could not be scaled at will.
generate quotes for company certifications automatically, without handing over professional responsibility. The initiative ran from February 2018 to October 2019.
the AI solution was trained on ten years of historical quote data and built together with a specialised implementation partner. Those historical quotes were not a side input but the foundation – without that data basis the initiative would have had nothing to stand on.
Scenaryo held the programme together and set its direction – leading a young UX/UI team, framing the AI team's work, working closely with a business analyst and marketing the results inside the group. The CIO was the client, with backing at C-level.
a weekly steering committee with the CEO, CFO, head of IT and the division lead of the operating company accompanied the initiative. Generated quotes did not go out unchecked – specialists reviewed them before they reached customers. Human-in-the-loop was not a later requirement but part of the design.
three things from this project still hold for GenAI initiatives today. First, human-in-the-loop is the reason an AI system in a regulated environment is allowed into production at all – not a brake but a precondition. Second, a weekly C-level steering committee sounds like overhead but is the mechanism that makes decisions fast rather than slow. Third, historical data is the foundation. Without it, or without the ability to prepare it, you do not have an AI project but a data project – and the sooner that is acknowledged, the better.
Related
Vibe Coding is almost free to start – but the bill arrives later: token burn, maintenance tax, security cleanup. Beyond a crossover point, Agentic Engineering delivers 3–10× lower TCO per feature. The decisive lever is total cost of ownership, not startup cost.
Open detail pageVinko Novak contrasts AI as search replacement with AI as delegation and argues that many teams confuse feeling faster with operating near the actual frontier of speed.
Open detail pageA compact overview of around 50 slash-commands in Claude Code – what they do, when to use them, and how they accelerate the AI coding workflow.
Open detail page