How we pick cofounders: the venture studio playbook
we don't take every deal. here's how we evaluate founders, ideas, and markets before committing to build a company together.
Feb 12, 2026

we get 10-15 partnership applications a month. we take 1-2.
not because we're trying to be exclusive. because we're committing years of our lives to every deal we take. if we're going to build something, it has to be worth the time, the risk, and the opportunity cost.
here's exactly how we evaluate every partnership that comes through.
we look at the founder first
the idea doesn't matter if the person behind it isn't right.
domain expertise. you know your industry cold. you've worked in it. you understand the customer because you've been the customer. you know what's broken, why it's broken, and who would pay to fix it.
distribution. you have access to the people who would buy this. existing relationships. an audience. a network. a sales channel. we don't partner with people who have to start from zero on customer acquisition.
grit. building a company is a 3-5 year commitment minimum. we need to know you'll show up when it's hard, not when it's fun.
what we're not looking for: technical skills (that's our job), a perfect pitch deck (decks don't ship products), or someone who wants to "ideate." we build. if you're still exploring, come back when you're ready to commit.
then we evaluate the idea
not every idea is a business. not every business is worth building. here's how we filter.
is there a paying customer today? if someone is already paying for a worse version of this, the market exists. if the idea requires "educating the market," it's a no.
is the problem expensive? the best businesses solve problems that cost real money. manual workflows that burn 20 hours a week. processes that require 3 people when AI handles it in minutes. if the pain isn't expensive, the solution won't sell.
is AI the right solution? we're an AI-native studio. if the problem is better solved with a spreadsheet and a VA, we'll tell you that. we're looking for opportunities where AI creates a 10x improvement, not a marginal one.
is the market big enough? we don't need a $10B TAM to get excited. but we need to see a path to $5M-$10M in revenue within 3-4 years. that's the bar for a partnership to make sense for both sides.
how the deal works
we don't charge dev fees. we don't invoice monthly. we take equity.
the split depends on what each side brings. there's no standard 50/50 or 70/30. we evaluate based on who's contributing what, who's taking on risk, and what the capital needs look like.
if you bring the market, the customers, and the domain expertise, and we bring the product, the engineering, and the systems, the split reflects that.
the principle is simple: same risk, same upside. we don't win unless you win.
what kills partnerships
we've learned this the hard way.
unclear roles. if both cofounders think the other person is handling sales, nobody handles sales. we define who does what before writing a single line of code.
no customer contact. if the non-technical founder isn't talking to customers weekly, the product drifts. we build what the market wants, not what sounds good in a meeting.
scope creep. the fastest way to kill a startup is to build 10 features when you need 1. we ship an MVP, get it in front of users, and iterate based on real feedback. not hypothetical roadmaps.
misaligned timelines. if you want a product in 2 months and the right product takes 6, we'd rather pass than rush something that doesn't work.
the venture studio model
venture studios have a 30% higher success rate than traditional startups. not because the ideas are better. because the execution is de-risked from day one.
the studio model removes the biggest risk for non-technical founders: building the wrong thing with the wrong team.
we run multiple ventures simultaneously. commercial lending platforms. SBA lending products. medical publishing systems. AI marketing engines. each one started the same way. a founder with domain expertise. a market they understood. a problem that was expensive and manual. and us as the technical team building it from the ground up.
how to know if this is right for you
answer these three questions.
do you know your industry well enough to sell the product before it's built?
do you have relationships with 10+ people who would be your first customers?
are you ready to commit 2-4 years to building this?
if the answer is yes to all three, we should talk.
apply for partnership → agentintegrator.io
Latest Articles
the biggest AI opportunities aren't in startups. they're in mid-market companies with messy ops, real cash flow, and problems worth automating. here's the play.
Feb 14, 2026
a free github repo turns claude code into a full marketing team. CRO audits, landing page rewrites, email sequences, and programmatic SEO. here's the setup and what it produces.
Feb 16, 2026

