the biggest software companies in the world started as internal tools that nobody planned to sell.

slack was a chat tool for a game studio. AWS was amazon's internal server infrastructure. shopify was a snowboard store's checkout system. basecamp was a web design agency's project tracker.

every one of them became worth billions. and the pattern is repeating right now with AI.

the origin stories

stewart butterfield's team at tiny speck built an internal chat tool while making a video game called glitch. the game failed. the chat tool got 8,000 sign-ups within 24 hours of beta launch. salesforce bought slack for $27.7B in 2021. revenue had hit $902.6M with 86.5% gross margins.

amazon's engineering teams kept rebuilding the same infrastructure. at a 2003 executive retreat, they realized they'd become experts at running reliable data centers. they opened it to the public. AWS now generates $107.6B per year in revenue with about 31% global cloud market share.

tobias lutke wanted to sell snowboards online in 2004. existing e-commerce tools were terrible. he built his own using ruby on rails. the platform was more valuable than the snowboard business. shopify now has 2.49 million merchants doing $292B in transactions per year.

37signals was a web design consultancy that built a project management tool to manage client work. basecamp launched in february 2004. by 2005, it was their primary revenue source. they abandoned consulting entirely. bonus: ruby on rails, extracted from basecamp's codebase, became one of the most influential web frameworks in history, powering github, airbnb, and coinbase.

why this matters for service businesses

when you build AI systems for a specific industry, patterns emerge fast. the insurance agency renewal workflow looks like the property management lease renewal workflow. the construction subcontractor communication system works for every contractor on procore. the medical intake automation works for every clinic running the same EHR.

the tool you build for one company starts working for 50.

MIT sloan calls this the "productization ladder": custom services, productized services, product-enabled services, then products-as-a-service. each step up increases margins and scalability.

the valuation math changes everything

a service company trades at 1-3x revenue. a SaaS company trades at 5-8x revenue. same team, same work, same customers. the company with productized IP is worth 3-5x more.

SaaS capital's 2025 data shows the median private SaaS company trades at 3.8x revenue. SaaS companies with margins above 80% trade at 7.6x. with net retention above 120%, that number hits 11.7x.

veeva systems is the clearest example. founded in 2007, targeting life sciences with vertical SaaS built on salesforce. 2024 revenue: $2.45B. market cap: $34B+. called the biggest vertical SaaS success story of all time.

procore did the same in construction. $780M revenue. $1.2B+ ARR. the CEO has been building for 23 years.

the AI version of this is happening now

the vertical SaaS market is worth $123-167B in 2025 and growing at 12-16% annually. over 250 M&A deals in vertical software happened in 2024. PE firms accounted for about 60% of SaaS acquisitions in 2023.

AI accelerates the cycle. engineering teams spend 30%+ of their time building internal tools. AI cuts that time in half. the tool that used to take 6 months to build takes 6 weeks. the tool that used to serve one client gets deployed to 10 in the same timeframe.

every service engagement is a potential product. every client workflow is a potential platform.

how we think about it

when we build for a client, we're always looking for what generalizes. the system that handles intake for one insurance agency. the AI agent that manages lead follow-up for one construction firm. the reporting automation for one healthcare practice.

if it works for one, it works for 50. that's the platform play. and it's why we take equity in ventures instead of charging fees and walking away.

whether you run a service business with repeatable workflows or you see a product inside your operations, the first step is the same.

book a call → agentintegrator.io