In the high-stakes world of M&A, the best deals are often found through proprietary relationships, not public databases. Sealk.co is betting that AI can finally digitize that serendipity, transforming a chaotic sea of unstructured data into actionable intelligence for dealmakers.

"Sealk isn't just indexing the web; it's reading between the lines of corporate press releases and financial filings to surface deals that traditional keyword searches miss entirely."

The traditional M&A sourcing playbook is broken. It relies on manual Google searches, stale industry lists, and luck. Sealk uses NLP to scan millions of data points—earnings calls, press releases, and patent filings—to identify companies that fit specific acquisition criteria (e.g., 'growing SaaS companies in Europe with recent founder departures'). It’s less like a search engine and more like a digital analyst.

• Proprietary AI models trained specifically on corporate financial language.
• Deep integration with Datasite's existing deal ecosystem.
• Focus on 'off-market' targets rather than public auction processes.
• Lean team structure suggests high margins and efficient R&D.