The Problem
Before they arrive
Buyers search on Google and ask AI assistants like ChatGPT — and your content isn't there to be found or cited, so they never reach you in the first place.
After they arrive
Visitors land on your site and still have to dig through menus and scattered pages to find what they came for. Many give up — and your support team answers the same questions over and over.
The cost
Hard-won visitors leave without acting because the content that would move them toward a decision isn't there, or isn't clear enough to be useful.
The root cause
Without knowing what users actually ask, search for, and fail to find, content decisions are guesswork. The gap between what you publish and what people need keeps growing.
How it works
Raffle starts from the real questions your users ask — not from rankings or keywords like an SEO tool, and not as another support inbox. Search and chat sense what people need, insights reveal what's missing, and you get direction on the content that serves them.
The sensor
On-site AI search and chat help users get answers instantly — and capture what they ask, search for, and can't find. That proprietary signal is what makes everything else work.
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The engine
Raffle turns the sensor's signals into a clear read of what content is missing, weak, or underperforming — and what to improve next.
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The deliverable
Get direction on the content that will serve your users, structured the way search and AI answers reward. We flag and recommend what to build — we don't write it for you.
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How it works
+23-42%higher conversionsRaffle Search handles the user journey and makes relevant content visible at the right moment, so more visitors find answers faster with a higher probability of converting.
28%longer session duration
2xbetter-qualified leads
24/7instant self-service answersRaffle never sleeps or takes a break. Your users resolve their own questions on-site before they ever need to reach support.
Latest news
Inside the mind of our co-founder, Prof. Ole Winther
In part I of this post I described how I got into artificial neural networks and machine learning research. The story ended with an AI winter. But after winter comes spring… The deep learning revolution A few stubborn researchers including Geoff Hinton kept true to the so-called connectionist paradigm. In 201…
Jun 1, 2026
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