A guild of AI-agent specialists. We take the one process eating your team's time and build the system that runs it — then build the software underneath it. Same method, run again in the next vertical.
Who you're dealing with
We're an AI-native studio that learned what worked from building and running a real AI product from zero to profitable — no funding, no ad spend, no shortcuts — and we've turned that into a playbook that runs the one process eating your team's time, end to end.
Every vertical we build runs the same six parts: a clearly defined unit, an intake form instead of a sales call, a rulebook for what "correct" means, a review layer that decides what ships automatically, a dashboard instead of an account manager, and a price against the human alternative — never an hourly rate. That's what makes it a studio, not a portfolio of one-off builds.
Senior-only, building end to end. No juniors carrying the workload, no layer of account managers between you and whoever's actually shipping.
What we build five to eight weeks, typically
AI foundations
A straight answer on what's worth automating first, before any build starts.
1–2 weeksWhere your process actually breaks, and what order to fix it in.
1–2 weeksAI development
The process that used to need a person now runs itself. Intake, quoting, triage, reporting, follow-ups.
2–4 weeksLeads route, follow-ups send, data cleans — without anyone touching it.
2–4 weeksA working v1, built fast, AI-leveraged the whole way through.
4–8 weeksProduct & engineering — scoped downstream of an agent build, not a standalone hourly offering
The app, site, or desktop tool underneath the agent.
scopedThe interface layer, built to be used daily — not demoed once.
alongside buildThe data model and handling underneath it. HIPAA-aware where you need it.
alongside buildWhy now
Y Combinator named this category in 2026: AI-native service companies that don't sell software — they sell the outcome.
AI runs the repeatable layer; senior operators govern strategy, exceptions and accountability. That is the model we already work in. Investor Greg Isenberg puts the category at a $100B opportunity inside a $4.6T services market — we're not betting on one slice of it, we're running the same studio model across several.
Figures are published industry benchmarks for AI-native agencies, not our own results.
The real moat isn't the model. Everyone has the same model.
It's the rulebook — every mistake caught and written down until the system stops making it. DilKiBaat's clinician-matching rules weren't designed on a whiteboard. They were written one real mismatch at a time, across 2,000+ real conversations. That's the method every Vertical Guild vertical runs on.
How it runs agent build, four weeks
Find the single thing actually eating your team's time — and prove it's the right one before anyone writes code.
The agent, and whatever software it needs to stand on, gets built and tested against your real work.
It ships, it runs itself, and it's handed over with nothing left half-finished.
Before you ask
No — we own the mistakes. Low-stakes work ships automatically; anything with money, legal, or reputational exposure gets a human check before it goes out. The model is the same one everyone has. The rulebook — hundreds of edge cases caught and written down for your specific process — isn't.
Most AI agencies point a model at your process and leave everything else the same — scoping calls, account managers, hourly billing. We collapse that on purpose: a form instead of a sales call, a dashboard instead of a manager, a price against the human alternative instead of an hourly rate.
If you can name it in a sentence, that's a real conversation. If the answer is "we're exploring AI," it probably isn't — yet.