Summary

We built an internal AI-powered platform that automates the analysis and report generation for our customer assessments. What used to take days of manual work now takes minutes, meaning we can get actionable insights in front of our customers sooner and start helping them faster. The team’s expertise stays central; the AI just removes the bottleneck.

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Background

When we work with a customer to assess how mature their data management is, or how ready they are to adopt AI, there’s a lot of manually compiled information that goes into it. Multiple people across their organisation answer detailed questions about topics like data governance, data quality, security, and strategic priorities. Each role brings a different perspective.

Problem

Making sense of all those responses is where the real work starts and traditionally, the process is slow. A consultant sits down with a stack of survey responses, reads through each one, cross-references answers, identifies patterns and gaps, calculates scores, and writes up a report. Depending on the size and complexity of the assessment, this can take days — sometimes weeks. And the longer it takes, the longer the customer waits before they know where they stand and what to focus on.

We asked ourselves: what if we could compress that timeline without cutting corners?

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What we built

We developed a secure, internal platform that uses AI to do the heavy lifting of assessment analysis and report generation. Here’s what it looks like in practice:

Customers complete the assessment
Answering questions across key areas like data governance, architecture, security, and AI readiness(based on DMBOK).

AI analyses the data and generates the report
Instead of a consultant manually interpreting every response, our AI engine reads across all the inputs, calculates maturity scores, identifies strengths and gaps, and produces a comprehensive, executive-quality report.

Platform aggregates all responses
Pulling together answers from multiple stakeholders into a single view, so nothing gets missed.

We review and deliver
The team reviews the AI-generated report, adds any additional context or recommendations, and delivers it to the customer.

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What’s changed

⚡Speed. What used to take days of manual analysis now takes minutes. The AI processes all responses, scores them against a structured framework, and produces a multi-section report, covering everything from high-level summaries to detailed, theme-by-theme breakdowns, in a single pass.

✅ Consistency. Every assessment is scored against the same criteria, using the same methodology. There’s no variation depending on which consultant happens to write the report that week. The framework is embedded in the tool.

🔎 Depth. Because the AI can process all responses simultaneously, it picks up patterns across stakeholders that might be easy to miss when reading through responses one by one. For example, it can flag where leadership and front-line staff have very different views of the same capability, that kind of insight is gold for the customer.

🗣️ Earlier conversations. This is perhaps the biggest benefit. Because we can turn around the analysis so much faster, we can get in front of the customer sooner, while the assessment is still fresh in their minds, and start the conversation about what to do next. We go from “we’ll have your report in a couple of weeks” to “let’s talk about your results.“

Why it matters for our customers

At the end of the day, the assessment isn’t the deliverable… it’s the starting point. The sooner a customer understands where their gaps are, the sooner we can help them close those gaps. Whether that’s strengthening their data governance, improving data quality practices, or getting ready for AI adoption, the value is in acting on the insight, not waiting for it.

By using AI internally, we’re not replacing the expertise of our team. We’re freeing them up to focus on the part that actually matters understanding the customer’s unique situation and helping them move forward.