Research should compound, not disappear.
Insights teams have spent years learning things about their customers that no general-purpose AI model could inherently know.
Why customers chose one product over another. What made them leave. How they reacted to a new concept. What they said in an interview three years ago that suddenly matters again today.
That knowledge exists, but the problem is finding it when you need it.
Research gets commissioned, analyzed, presented, and stored. Reports end up in folders. Transcripts live somewhere else. Teams and vendors change. And eventually, some of the most valuable customer knowledge an organization owns becomes difficult to find and even harder to put back to work.
As AI becomes embedded in how insights teams work, there’s an opportunity to change that. Not simply by generating more research or faster answers, but by making the customer knowledge organizations have already created easier to access, easier to verify, and more useful over time.
As we work with insights teams navigating this shift, the same challenges keep surfacing.
Research shouldn’t expire when the project ends.
A study gets completed, the findings get shared, and the decisions get made. Six months later, a different team asks a related question. Someone remembers there was a study. Someone else thinks they know where the deck lives. Maybe the researcher who ran it is still there… and maybe they aren’t.
And sometimes, research that didn’t seem particularly important at the time becomes relevant in an entirely new context. A finding that didn’t make the final deck may suddenly matter when the market changes, a new product launches, or a different business question emerges.
The organization may already have valuable context. It just doesn’t know where to look for it.
Research findings shouldn’t have a shorter shelf life than the decisions they influence.
Your AI doesn’t inherently know your customers.
AI can bring an extraordinary amount of outside knowledge into a conversation. It can understand your category, summarize trends, analyze information, and help researchers move faster.
But it doesn’t inherently know what participants said in a concept test two years ago. It doesn’t know why customers responded negatively to an earlier version of a product. It doesn’t know what your team learned across years of research.
Your organization does.
As AI becomes another way people find information and answer business questions, the opportunity is to close the gap between what AI knows about the world and what your organization knows about its customers.
You can’t act on what you can’t verify.
Making that knowledge accessible to AI creates another question:
Can I trust where this came from?
AI can generate a convincing answer in seconds, but research teams have a higher standard.
If something is going into a presentation, influencing a recommendation, or informing a major business decision, researchers need to be able to inspect the evidence and get back to the research behind it.
The new rule for AI in research should be simple:
Show your work.
A fluent answer isn’t the same as defensible research.
FC Repository gives your research a home.
FC Repository is designed to give the research your organization has already created a home where it can keep working for you.
Bring existing research into Repository and it becomes searchable and accessible to your AI assistant. Ask a question in natural language, and Repository can surface relevant material from your organization’s research and return the originating research file alongside it.
The original research stays intact. It remains the record.
And that distinction matters.
Every result FC Repository returns is designed to be traceable to a retained research file that can be opened and inspected. If a result can’t be traced back to a retrievable file, we consider that a failure.
We’re also deliberate about what that does and doesn’t mean.
We won’t call AI “hallucination-free.” When a third-party AI assistant is generating the final response, no responsible platform can guarantee every word that assistant produces.
What we can do is make sure the research FC Repository returns is grounded in a source you can actually open.
That’s the standard we think research AI needs: not just an answer, but evidence.
Starting with the foundation
FC Repository is currently in alpha, and we’re intentionally starting with the foundation: making the research you’ve already created easier to find, accessible to AI, and traceable back to its source.
Because the long-term opportunity is much bigger than searching old research.
It’s an insights organization where years of customer conversations don’t become forgotten transcripts. Where research that seemed minor when it was conducted can resurface when a new question makes it relevant. Where AI doesn’t just know your industry, but can access the customer knowledge your organization has spent years building.
And where researchers can always get back to the evidence behind what they find.
Research should compound, not disappear. FC Repository is the foundation we’re building to make that possible.
Get Early Access to FC Repository
We’re opening FC Repository to a limited group of insights teams. Alpha participants can put their existing research to work with AI today, while getting an early look at where we’re taking Repository next.
