The deal you miss is usually the one you found too late.

The deal you miss is usually the one you found too late.

Corporate venturing is still a pile of decks, a CRM of old partnerships, and a team that cannot read all of it. A model can sort faster than a competitor who is still skimming. It will not pick the partner. It will get you to the ten you should actually call.

You already have the file: old deals, who you partnered with, market notes. Sales, product, money, position, reviews. Clean that into one profile per startup or the score will sound sure and be wrong.

Teach it your wins. Then let it find the weird ones.

Show it partnerships that worked: product fit, values, a return in a window you care about. Tech, team, funding, growth, city. That is supervised, which is just "here is what good looked like." Unsupervised is the other pass: team mattered more than zip code, loyalty beat revenue. Fast product shops in one pile, distribution-hungry incumbents in another. Comments and mood, not just the spreadsheet.

Start small. Who is likely to take your terms. Who is actually growing. A few hundred past ventures is enough to try. Split train and test so you know if it is guessing. Thin file? A language model and a sheet of industry, stage, headcount, revenue, and stack can still rank fit.

Keep the scan on. You do the relationship.

News, raises, launches, new markets. Pull revenue, bios, and product from the deck so a person is not doing that by hand. An 85 percent fit is a lead, not a yes. A hundred names in the time you used to spend on ten. The team talks and negotiates. The model does the sorting you were already late on.