Right now, your customer feedback is telling you exactly what’s wrong – and you’ll never read it.
Not because you don’t care – but because the feedback is so diverse and volume is overwhelming. Thousands of reviews, survey responses, support tickets, employee comments, interview transcripts, and open-ended form fields pour in constantly. There’s simply no practical way for a human team to read through all of it, find the key patterns, and turn those patterns into action. So most of that data sits untouched, a goldmine that never gets mined.
It seems like AI should be able to solve this problem. After all, AI can read all of your data. But if you’ve tried feeding your data into an AI system and asking for answers, you probably didn’t get what you wanted. An ordinary AI will just hallucinate, and a RAG system can’t find patterns that only emerge over thousands of records.
What you need is not a smarter prompt, a bigger model, or a more sophisticated RAG system. You need a system that was designed from the ground up to listen for patterns over vast swathes of data. You need a system that reads all your documents to identify your problems, determines which problems are driving the selected KPIs, and writes a report on each one – with citations from the data to verify that it isn’t hallucinating.
This is exactly what we have.
