Jakub, I think I’m unusually well suited to this because organising chaos has been a recurring theme throughout my career. I’ve spent 25+ years across technology, product, leadership and building companies, including M&A. Give me a messy system with too much information, unclear structure and things falling through the cracks and my instinct is to map it, find the signal and make it work better. I’d approach Community Funded Research the same way. First, I’d learn the existing structure properly and do enough of the work manually to understand the judgement behind it. I wouldn’t automate a taxonomy I don’t understand. Then I’d start looking for repetition. - What are we reading over and over? - What are we categorising manually that follows a pattern? - What keeps going stale? - What useful information gets buried in discussions? - What connections between people, companies, talent and opportunities are easy to miss when each item is looked at separately? That tells us what to hack first. I’d use AI heavily for the mechanical work: reading, extracting, suggesting categories, finding duplicates, checking for stale information and looking for connections across discussions. But I’d want every useful piece of intelligence traceable back to where it came from, and I’d keep judgement over what deserves to enter the knowledge base. The part that interests me most is what happens after you get the basics right. A great person keeps appearing in high-quality discussions. Talent Scouting should notice. Five members independently mention the same problem. That’s probably worth looking at. A company starts appearing across discussions, people and opportunities. Why? Something buried in a conversation six months ago suddenly becomes relevant to an acquisition or partnership today. Can we find it? That’s the kind of system I’d want to help you build. And I wouldn’t arrive with a grand architecture for it. Give me the current system and a pile of the raw chaos.

@Jakub Pacanda it requires market research, but its standard funnel definition. Based on what people type in Google, YouTube and TikTok (3 largest search engines) we can define the funnel. Fairly sure we would need to educate certain demographics before warming them up for any (investment) business.