As a company scales,
customer needs become
harder to pin down.

Intuifi shows you what all of your customers are telling you,
so you can decide what's next.

Request your first free report
Problems leaders face

Customer insights are siloed and patchy. Getting the full picture requires effort.

Strategic planning relies on filtered departmental end-of-quarter reports.

Using AI saves you time, but without the evidence it is hard to trust the output.

Intuifi
What you get instead

See a unified view of customer notes captured across your existing tools.

Know what customers need so you run informed strategic planning sessions.

Every finding links back to the source, so you can verify whatever you need to.

Understand what ALL of your customers are telling you,
not just a select few.

No commitment required.

Files are deleted as soon as the report is generated.

Want to see what you get?

Check out this anonymised example →

The person behind this

Chris Burgess

I am Chris Burgess, a product leader with 15 years of experience across startups, scale-ups, and a Fortune 100 company. I built Intuifi because I kept seeing how hard it was to connect customer feedback to real strategic decisions. Insights were scattered, summaries lost context, and teams were left debating what customers actually needed. Too often, decisions were made on assumptions instead. I wanted to fix that.

Learn more about me Connect with me on LinkedIn Read my articles on product strategy

Frequently asked questions

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How does it actually work?
Upload CSVs from multiple tools your team already uses - such as combining your CRM and support platform. Intuifi analyses everything across all your files, identifies the recurring themes, patterns and tensions, and produces a structured report. You start with a high level summary and can drill down into the evidence behind any finding whenever you need to.
What effort is involved and how much of my time does this take?
Simply ask your team to export the data from the tools they are using. Then upload those files in a few clicks and sit back while the analysis happens. There is nothing to configure and no prompting required. Around five minutes later you will get back a structured report with an executive summary, the key themes across your data, and the evidence behind each one. From there you can share it with your team, use it to prepare for a planning session, or just keep it as a reference point.
What results can I expect?
The report opens with an executive summary of the key themes and tensions across your data. Each theme comes with supporting evidence, an implication for your business, and signals to track. Everything links back to the source so you can verify what matters. To see exactly what you get, take a look at this sample report.
This looks like a manual process. Why?

This is an MVP and the decision to keep it manual is deliberate. I am looking to build trust, and the way I am approaching that is to reduce any concerns you might have about your data, by enabling you to edit or sanitise anything you want to upload before it reaches Intuifi. Automation is coming, but only once I am confident you are getting the insight you need.

Here is where Intuifi is heading:

Now

On-demand reports

Upload your data, get back a structured report with themes, priorities and evidence.

Next

Automated data ingestion

Connect directly to the tools your team already uses.

Pattern memory

Track how customer themes change across reports over time.

Continuous monitoring

Alert your team when new trends emerge.

Later

Interactive discovery

Ask follow-up questions and let Intuifi investigate for you.

Contextual input

See how market needs align with your business goals.

Strategic simulation

Explore how market headwinds could reshape your priorities.

How is my data handled?
The files you upload are processed to generate your report and then deleted. Nothing is stored, nothing is retained, and I never see your data at any point. Intuifi does not train on your data.

For more information:
Anthropic data usage
MindStudio privacy policy
How accurate is the output?
That depends on the quality of the data you upload. Intuifi analyses what is there and surfaces the patterns it finds across it. It will not always get every theme right, and some findings may reflect noise rather than signal. That is why every finding links back to the source data, so you can check what looks right, discard what does not, and act with confidence on what remains. The analysis is a starting point, not a verdict.
How is this different from a typical dashboard?
This is not another dashboard. Dashboards usually present quantitative data and leave the interpretation to you. Intuifi works differently. It takes qualitative feedback like interviews, support tickets, survey responses, and call notes, then turns it into a structured report with clear themes, strategic implications, and the evidence behind each one. You are not exploring charts. You are seeing what customers need, and why it matters.
Why would I not just use ChatGPT or Claude?
LLMs give you good answers when you ask the right questions. But as a leader, you should not have to become a prompt engineer to understand your customers. You still have to prepare your data, structure your questions, interpret the output, and turn it into something another person can review and trust. Intuifi removes that work. Upload your files as they are and get back a structured report with themes, priorities, and the evidence behind every finding.
Could I not just build a tool like this myself?
Vibe coding tools make it easier than ever to build something that generates an output. The harder part is making it consistent and trustworthy enough to share with your team and act on. Intuifi is designed around that standard, so you spend less time maintaining workflows and more time understanding what matters.
Won't this become obsolete as AI improves?
The opposite. As AI becomes more capable, so does Intuifi. The methodology that structures your data, preserves the evidence, and produces something your team can trust is built on top of AI, not instead of it. A more powerful engine makes the output better, not unnecessary. What stays constant is the structure that makes the insight trustworthy and actionable.