The Growth Operating System
for AI Companies

Most companies trying to use AI for growth hit the same wall: their data is fragmented. Product signals in one tool, billing in another, support in a third, CRM somewhere else. Ten disconnected systems, none talking to each other. So when they add AI, it hallucinates - because it has no coherent context to reason about.

That fragmented stack is also why most companies need 4-5 hires just to operate their commercial engine. The bloat isn't in the team. It's in the technology.

PATCH eliminates both problems. One unified system replaces the entire stack. Product, customer, revenue, operations - every dimension of the business connected in a single data model, custom-built for each client's specific growth goals. Growth intent goes in. Direct outcomes come out.

On top of these foundations, we build entirely custom tooling and interfaces for each client. Every team member gets access to the same context - with appropriate security boundaries - which means entire teams are enabled, not just the person who knows where to find things. Walls of friction break down. The result: teams end up with a hyper-simplistic method of working that fits them like a glove. No training manuals. No six-month rollouts. And because everything is code, we iterate aggressively toward their growth goals without bottlenecks or silos. Over time, their growth operations become a genuine moat.

This also future-proofs every team that adopts us. The entire system only benefits from incremental improvements in the underlying models that power it - redundancy is skirted by design. Our clients don't have the capacity or incentive to stay current with every shift in AI tooling, and they shouldn't have to. We insure them against it. Any platform that locks itself in the sand becomes irrelevant the minute a better general release ships. We pivoted early and pivoted aggressively with our clients to stay ahead of that curve - and it's why we're here.

Everything we build is legible to both AI and humans. We've figured out how to make large, complex datasets coherent and queryable - with interconnected infrastructure that's entirely interfaceable through natural language. There is no limit to what can be asked or built on top. It took thousands of hours of architecting and iteration to make this possible. We now have leading GTM agencies approaching us to partner because they can't crack this problem - they still resort to stitching together redundant software tools to approximate what PATCH does natively.

Series B · $100M+ raised · 120+ employees · 100M+ patient interactions

Healthcare sits at the frontier of AI regulation. Corti builds AI for clinical decision-making - where compliance teams scrutinize every data flow. Our system had to pass 30+ page AI impact assessments and DPIA reviews before going live. It cleared every hoop and went into production.

Discovery to company-wide deployment in 30 days. The co-founder hard launched the system to the entire company. Organic adoption across the full team - no training, no mandates. They just started using it.

Co-founder hard launches the system company-wide: "everyone can make serious impact"

Andreas Cleve, Co-founder

VP requests a complex cross-system data pull

"LEGIT GAME-CHANGER ALERT. Solved in ~10 seconds."

Atlas is what Corti's team named the custom agent built on their system. Not a generic chatbot - an interface shaped entirely by their data, their context, and their growth goals. That level of contextual awareness is only possible because of the aggressive data centralisation underneath. Every client's system works this way. Teams name the tools. They make them theirs.

Co-founder proactively requesting automated intelligence reports. Team responding: "THIS IS ALREADY IN THE WORKS." Organic adoption - the team is driving their own requirements.

Series B, $100M+	"The missing piece for our $50M fundraise"
Series B, $1B valuation	Replaced their entire enrichment stack. What took 5 days now takes 5 minutes
Series A, $650M valuation	Enterprise buyers surfaced from self-serve signups for the first time
Series A, $44M raised	Full growth engine deployed. Outbound generating pipeline
Series A, $1B+ AUM	Growth system in a regulated financial services environment
YC W24	Healthcare AI. Usage-based growth intelligence

30+ companies. 100+ growth motions deployed. Healthcare, fintech, developer tools, AI infrastructure.

Alex is a Cape Town native. 2 of 3 current operators are already SA-based. The operator role is the key to this model - high-value, systematic, trainable. Not freelance gig work. A real professional path building growth systems for global companies.

AI development has leveled the playing field. An operator in Cape Town delivers the same quality as one in London. The clients care about outcomes, not geography.

This is not an AI automation agency. We don't cobble together disparate workflows or compromise on the foundation. PATCH replaces the full growth operation - and we only work with companies that are ready for it. We're selective because the model demands it: clients need to be receptive to a fundamentally different way of working. The ones that are? Every competitive demo we've run against 7+ traditional proposals has closed. Every one.

Everything to this point has been built in private. No marketing. No outbound. Every client has come through referrals and partnerships. That was deliberate.

We've been in client-funded R&D mode since the pivot - making a bet on the future of AI growth operations while the rest of the market was still selling SaaS seats. Our clients funded the iteration. The real-world problems shaped the system. The result is a proven model with proven economics and a client base that keeps referring us.

We're ready to go to market now. We can continue to self-fund and bootstrap with the support of our clients - the unit economics allow it. Or we can partner with influential entities and advisors who share a similar view of where the economy is heading and want to be part of shaping it.