Systems | Development | Analytics | API | Testing

86% pick generative AI before any BI tool for analytical work. Trust ranks fourth in their reasons. Speed and convenience rank first.

Connecting Salesforce to Claude via MCP is the advancement the SERP says it is. You authenticate once, your AI agent queries live CRM data, and you stop copying deal records into chat windows. For a Revenue Operations Manager who spent Q1 begging an admin to export pipeline snapshots, that matters.

The pricing page tells you what Free includes. This piece tells you whether Free fits how you actually work.

The decision is not which product to choose. It is whose performance you are reporting on.

Most agencies compare plans by scanning feature grids. The ones that pick the right plan on the first try do arithmetic instead.

The plan that fits your workflow is rarely the one you land on if you shop the pricing page first.

A year ago we announced that Databox is becoming an AI-first company. At the time, that mostly meant what it meant for many companies in 2025: AI becoming a strategic priority. Teams were encouraged to experiment and adopt new tools, as it was clear that AI wasn’t a trend we could ignore. That was the easy part. What’s become clear over the last year is that there’s a significant difference between being AI-first and being AI-native.

Every team we talk to has a running list of questions they wish they could get fast, reliable answers to. What changed in our performance last month and why. Which clients are showing the early signs of churn. Which channels are actually pulling weight and which ones are quietly burning budget. The pull toward AI for this kind of work is obvious. The answers should be a question away.

Ask three people in your company to pull the number of active customers this month, and you’ll probably get three different answers, even though each person labeled the metric the same way. One counts everyone who logged in, another counts only paying users, and a third filters down to a single plan tier. Nobody is wrong here. They’re all working from real data; they just never agreed on a single definition. Do that enough times, and the data itself becomes the thing everyone argues about.

A manual walkthrough, and the Claude skill that does it for you.