Getting Started with SellSide DB: Filters, AI Insights, and Research Chat

Step 1: Open the listings browser

Navigate to /sellside. You'll see a grid (or table view) of every active listing, with filter controls for category, country, asking price, profit multiple, TTM revenue, paying customers, and sort order.

We recommend starting with three filters: max profit multiple, max asking price, and minimum TTM revenue. Layer on category once you know which industries you're shopping in.

Step 2: Read a listing detail page

Click any listing to land on /sellside/[slug]. The page has six surfaces: hero (headline, asking price, multiples, status), metrics panel (TTM revenue, customers, churn, ARPU), AI insights (attractiveness, bootstrap score, risk and opportunity signals), qualitative fields (tech stack, competitors, growth opportunities, key assets, reason for selling), related listings, and a permanent link to the source marketplace.

Step 3: Read the AI insights panel

The AI insights panel is the buyer's-eye view. It surfaces two numerical scores - acquisition attractiveness (0–10) and bootstrap score (0–10) - plus an AI-written buyer thesis, a list of risk signals, opportunity signals, and explicit red flags.

Use these as your first-pass filter when reading dozens of listings. Anything below 6 attractiveness gets a fast skip; anything above 8 deserves a careful read.

Step 4: Open the research chat

Navigate to /sellside/research. The chat has five tools - searchListings, getListingDetails, getBenchmarks, getDealFlow, and semanticSearch. The last one is the most powerful: it runs vector search across listing content, so you can ask qualitative questions like 'listings with churn problems and a single power user persona' or 'agentic AI products with sub-10 customers.'

FAQ