AI For M&A: Seeking feedback from PE/Search Fund experts

My name is Daniel Edgar, student at Queens University majoring in computer science. During my first year at Queens I built an AI consultancy, pivoted to software, started pitching VCs and secured my seed round at a $2.3M pre-money valuation. We have an office Downtown, Toronto and and a strong team devoted to solving this problem: Acquiring an SMB is notoriously expensive, time-consuming, and risky. Buyers spend hundreds of thousands on due diligence and external consultants, yet deals still frequently fall apart because of hidden operational dependency. We are using our proprietary AI to give institutional buyers the operational clarity needed to de-risk deals, automate diligence, and compress the timeline and cost significantly. 80% of profitable SMBs never sell. We are currently in our validation phase and are looking to connect with people who experience this pain firsthand, not to sell them anything, but purely to learn and fine-tune our solution. Specifically, we are trying to connect with: Middle Market Private Equity firms (PE Principals or VPs doing SMB roll-ups). - To identify high level pain points and biggest expenses in the process. Search Fund Principals (investors acquiring and operating a single SMB). - To identify the high level pain points and biggest expenses in the process. External Consultants/Diligence/Advisor teams who are deployed into those target companies. - To identify their key diligence workflows and the most time consuming pieces. Book a call if your interested in AI and fit this profile, we would love to learn from your industry experience. cal.com/nodebase redacted +###-###-#### Thanks so much for your time. Best, Daniel Edgar CEO & Co-Founder https://www.nodebase.ca