Customer-controlled
Your accepted scope defines hardware, account ownership, administrator access, licensing of what we build, documentation, backups, and recovery responsibilities. You know what you own before the work begins.
About Hatched Stacks
We build AI systems that businesses own and operate.
The founder of Hatched Stacks, Joseph Dawson, built this AI operating system to solve the same day to day challenges most entrepreneurs face when trying to build successful companies. Not enough hours in the week, too many repetitive tasks, and the work that actually grows the business getting pushed to next week again.
Building an AI operating system takes a lot of different skills, from understanding your business to designing how it all fits together to keeping it secure, and most firms cover that by passing you between people. You explain your business to one person, someone else builds it, and what comes back is not what you described.
So Hatched Stacks was created to solve that problem and become your business' AI operating system, where your business context, your tools, and your rules live in the system itself instead of in somebody's head.
Inside it, specialized AI agents each own one job. One researches, one builds, one checks the work. They share what they learn, so a decision you make once stays made instead of getting relitigated every time a new session opens.
We run what we sell, and we stand behind what it produces.
One workflow at a time
Every founding engagement starts with one measurable workflow. We observe the process you have today, define its baseline and its failure cases in writing, build the replacement beside it, run it in shadow mode against real work, and activate it only after you accept the results.
Nothing goes live because we say it is ready. It goes live because you tested it and agreed.
From there it compounds. The longer-term 180-day vision is that accepted workflows connect across sales, marketing, content, websites, apps, and operations, one at a time, each separately scoped, each with its own baseline and its own acceptance test.
What you are actually getting
The dedicated Mac is an operating anchor, not the product by itself. The value is everything defined around it: the implementation, the business knowledge encoded into it, model routing, agent roles, controls, evidence, documentation, training, and the operating model your team runs after delivery.
Workflow-specific
Claims, data boundaries, models, tools, permissions, and acceptance tests are defined for the workflow actually being built, not for AI in general.
Accountable end to end
The same operator qualifies the work, designs the system, builds it, and stands behind it at acceptance. Nothing gets handed off to a stranger halfway through.