Why now
Buyers stopped Googling. Most CI tools haven't noticed yet.
For builders, operators, and anyone with Cursor, Codex, Claude, or ChatGPT in their workflow, AI assistants have quietly replaced Google as the first stop for tool decisions. Every competitive intelligence tool on the market still measures the old channels. Korpora measures the new one.
The lived demonstration
We built Korpora after watching our own buyer behavior change without noticing. Every tool we picked to build the product came from asking an AI assistant. The deployment platform. The database. The data-pull API. The Twitter API. The secrets manager. The AI model SDKs. The PDF library. Every. Single. One. None came from Google. None came from G2. None came from a Reddit thread or a TechCrunch roundup or a LinkedIn post.
Real buyers making real tooling decisions worth real money. Zero of those decisions touched the channels every competitive intelligence tool measures.
Then we asked the obvious next question. If we're buying like this, how are the things we sell showing up for the buyers who buy the same way? Nobody had built the answer. So we built it.
Three shifts that already happened
Tool discovery moved from search engine to model
For developers, founders, and growth operators, the default first-touch when evaluating a new SaaS tool is now an AI assistant. Not Google. The recommendation arrives pre-summarized, pre-comparative, and skips the SEO-bait result pages that used to dominate. The category leader on Google is no longer the category leader on Claude or ChatGPT, and the gap between them is increasingly the strategic story.
Discovery framing is where buyer journeys begin
Most mindshare reports count how often a brand is named when you ask about it. Korpora splits that out. Organic AI mindshare is what the model surfaces unprompted in 'best X for Y' queries. Evaluation-stage share is what the model names when you explicitly ask 'tell me about X.' The spread between the two is the cold-start diagnostic. Brands with a wide spread look strong in headlines and are invisible in the queries where buyers actually start.
Training corpora compound on a quarterly clock
When a brand shows up in a viral Reddit thread or a high-engagement X post or an academic paper today, that mention enters the next model training cycle in 60-180 days. The AI mindshare you have now is downstream of the content density you produced 6-12 months ago. Investments in the right kind of content compound; investments in the wrong kind dilute. The right kind is technical, methodology-rich, ecosystem-participant content. The wrong kind is career-aspirational engagement-bait.
What this means for your team
Most marketing and CI teams are still optimizing for channels their buyers stopped using. Google rank, G2 reviews, share of voice across social: all useful, all incomplete. The buyer channel that already decides who wins in your category for the builder cohort sits below every CI dashboard currently in production. Until you measure it, you don't know whether you're winning the agent layer despite losing every traditional channel, or the inverse: winning traditional channels while quietly losing the layer that increasingly drives buyer-discovery.
That measurement is what we built.