You're buying AI in pieces. We design the whole thing.
Fixed scope. Fixed fee, quoted before anything starts. A standalone deliverable that's yours to own: take it to another implementer if you want to.
Member of the Claude Partner Network. Claude Certified Developer on the team.
One vendor takes your voice. Another takes your chat. Your operational system runs the units, and ticketing handles support. Every one of them works, and none of them was designed to sit next to the others. So the AI answers a call it can't price, the chatbot quotes what it can't reserve, and the reporting can't say which ad paid for either. The platforms ship the AI. They don't ship clean data, sane process, or the wiring between systems. That gap is the work. Vendors are paid to sell their slice. We're paid to design the whole operation.
Every system's data in one database you own, and every document, price and answer in one tagged place. Anything with an API reads from it. This is what the architecture designs and stage 03 builds.
Every system's data in one database, in your own accounts. PMS, front desk, phones, ads.
The connections that keep it current. Each system writes in and reads out on its own schedule.
Documents, SOPs, prices and answers in one tagged place, in Notion, ClickUp or Google Drive.
What reads from it: the voice agent, the chat, the reporting, the staff assistant. Anything with an API, through the Brain Connector.
They read from the Brain, not from ten systems. Swap a tool without starting over.
Staff and AI read the same data, in one format, with access control.
The answers live in the Brain, not in one person's head.
Live now at a couple of companies.
Current state map
Every system in the operation, what it does, where it connects, where it doesn't.
Target architecture
The recommended stack, component by component, with the reason each was chosen over the alternatives.
Component recommendations
Named products per job, best in class regardless of who resells them. Includes what we'd build and what we'd buy.
Prerequisites list
What has to be fixed before the AI layer works: data quality, process, FAQ consistency, integration gaps.
Sequenced roadmap
What to do in what order, with dependencies and costs per phase.
Walkthrough
A live session with the decision maker. Not a document dropped over the wall.
The target architecture for a multi-site self-storage operator, anonymised. No platform is named. Platform choices come after, scored against these requirements.
If the design fee were credited against the build, we'd be paid to design a big build. You pay for the architecture on its own, so we get paid the same whether the answer is a platform we resell or one we don't.
We recommend what fits, never what pays us. If the right answer is a tool we've never sold, that's the answer you get.
Diagnosis tells you what's broken. It doesn't tell you what to build. Stage 02 is the bridge: it turns the audit's costed picture into a named, sequenced design.
Multi-location operators with two or more AI or CX tools already in play and growth planned. The founder, CEO or ops director who signs platform decisions.
The platforms ship the AI. They don't ship clean data, sane process, or the connections between systems, and that's where AI projects fail. We design the operation the AI sits in, wire the platforms together, and fix the prerequisites first, so the AI you already pay for starts earning its keep.
Yes, and most clients should. The architecture tells you which one thing pays back first. You don't have to buy the whole roadmap; it's designed so each phase stands on its own.
If you want us to. Stage 03 is exactly that. But the design is built to be taken anywhere, including to another implementer or your own team.
Fixed scope, fixed fee, quoted before anything starts once we've seen the shape of your operation. The findings and diagrams are yours to keep either way.
45 minutes with Aaron. Bring the problem that's costing you the most. You leave with a view on what to fix first, whether or not you hire us.