While most acquirers rely on brokers, platforms like Craigslist or Facebook Marketplace can be a hidden source of off-market deals. Very small, less sophisticated business owners often default to these simple platforms to sell, creating unique opportunities for diligent searchers.

Before initiating contact, Prime Group's team conducts deep dives on target properties, researching rents, taxes, and other operational details. The goal is to understand the asset better than the owner. This level of preparation establishes credibility, demonstrates serious intent, and sets them apart from unsolicited, low-effort offers.

Anthropic's 'Project Panama' involved buying and physically destroying one million books to scan their pages. This expensive, analog process created a unique, high-quality dataset that is difficult for competitors relying on easily accessible digital libraries to replicate, forming a powerful and defensible competitive advantage in the AI race.

In an era without standardized reporting, Green created her own information advantage. She personally inspected assets like rail yards, talked to workers, and even found disgruntled associates of sellers to uncover hidden flaws. This deep, primary-source due diligence was her key differentiator from other investors.

To remove friction from acquisitions, Prime Group goes beyond the transaction and helps sellers solve their next problem: what to do with the money. By hand-holding them through maximizing their sale proceeds, managing tax implications, and planning their next steps, they build deep trust and turn sellers into a referral source.

Relying on inbound deal flow is like buying a house in a competitive market. The best deals, like off-market real estate, are found through proactive, direct outreach. This "hard work" of building relationships and creating opportunities leads to better terms and less competition.

As AI models become commoditized, the ultimate defensibility comes from exclusive access to a unique dataset. A startup with a slightly inferior model but a comprehensive, proprietary dataset (e.g., all legal records) will beat a superior, general-purpose model for specialized tasks, creating a powerful long-term advantage.

To build a unique dataset without massive cost, target the aggregated, non-identifiable 'exhaust data' from software, payments, and telematics companies. These firms often undervalue this data, which they may have been deleting, and might provide it cheaply or exclusively.

ReSeed's model is a heavy lift upfront but creates a powerful, decentralized deal sourcing machine. By backing numerous scrappy, local experts, they have boots on the ground in many markets, unearthing opportunities that a single, centralized acquisitions team could never find.