Systems | Development | Analytics | API | Testing

If you've just enabled Kai in your Keboola project, you might be wondering: "Okay, now what?" This guide walks you through your first conversation with Kai, following the same steps I demonstrate in my introduction video.

Last week we publicly released Kai, our in-platform AI assistant, a data engineering agent that can build integrations, write transformations, debug failures, and document your entire project. I'm extremely proud of the team and what we've delivered. Yes, everyone has an AI assistant now. But most are chat wrappers that look great in scripted demos and fall apart with real work.

Navigate to Workspaces → SQL Editor in your Keboola project. Write or paste your SQL query in the editor. ‍

You've outgrown Excel for consolidation. But what comes next? Anaplan starts at $200K+ - and still assumes your data is already clean. Your data team wants to build something custom - but "three months" always becomes twelve. And every vendor says they're the answer. This guide compares every realistic consolidation path side by side. Real costs, real timelines, real trade-offs. Including when staying with Excel is still the right call.

Your data team is confident. Your budget is approved. And building your own system still sounds like the smart, lean choice. This guide is for the CFOs who've been there - or who are about to be. Three chapters. Real costs. The two things every team skips in version one. And a decision framework you can actually use.

Your finance team wastes 14 days every month on manual consolidation. Your close stretches to 15-25 days. And you're one key person departing from chaos. The brutal math: Your "free" Excel process actually costs $850K+ annually in wasted time, errors, and missed opportunities. Meanwhile, leading multi-entity CFOs just cut their close time by 80% and freed their teams for strategic work instead of reconciliation hell.

"We were wasting too much time debating the accuracy of numbers as opposed to using that time to make decisions." That's how Satty Saha, Group CEO of CreditInfo-a credit bureau operating across 30+ countries-described the moment he realized his organization had a data problem. Not the kind of data problem you'd expect from a company whose business is data and analytics. An internal data problem.

It's 9 PM on Day 5 of the month-end close. Your controller is still at their desk, squinting at the intercompany reconciliation spreadsheet that refuses to balance. The German subsidiary's numbers came in late (again). The currency conversion formulas broke when someone accidentally sorted column B. And tomorrow morning, the CFO needs consolidated financials for the board meeting.

It starts innocuously. Marketing signs up for a new analytics platform. IT renews that enterprise license even though only 40% of seats are used. HR adds another recruiter. Travel spending creeps back to pre-pandemic levels despite hybrid work. Then one day: SG&A as percentage of revenue climbed from 22% to 28% over three years. Your margins are compressed. The board is asking questions.

Here's a statistic that should concern every CFO: according to 2024 research from Accenture, finance teams spend 85% of their time on data triage-gathering, validating, and reconciling numbers. Only 15% of their time goes to the strategic work they were actually hired to do. If that sounds familiar, you're not alone. The reality is that most CFOs today can't confidently answer a deceptively simple question: "Where did this number come from?".