Turn work that slows you down into an AI workflow built for your business.

A dedicated AI operating system for your business, built around your real workflows and running on a machine you control. It combines your organized business knowledge, task-appropriate model routing, and a multi-agent layer with defined roles, approvals, and exception handling in one governed system rather than a collection of separate tools.

A subscription gives each employee the same general assistant, without a shared memory of how your business actually runs. A Hatched Stack is configured around a workflow you select, works from your approved company context, and runs on hardware you own. You are commissioning a system built for your process instead of renting another general-purpose seat.

Operators with at least one recurring workflow that has a measurable baseline, a clear owner, and enough volume that improving it matters. Launch suits businesses starting with one workflow; Pro and Max provide more capacity and room to expand; Ultra is for qualified workflows that must run entirely on local models.

No. Your accepted scope defines access, documentation, training, and support before implementation begins. You will need to name a workflow owner, meaning someone who understands the process today and can approve how it should work afterward.

A dedicated machine sized to the workload: Launch includes a Mac mini with 16 GB memory and 512 GB storage; Pro includes 24 GB and 1 TB; Max includes 48 GB and 1 TB; and Ultra uses a Mac Studio selected after workload qualification. The machine is yours and runs in your environment. Additional specifications are available on request.

With you, on your network and power. It needs a reliable internet connection, uninterrupted power, and a place where it can stay on continuously so approved workflows remain available rather than starting only on demand.

Every accepted build includes backups, recovery documentation, and defined rollback paths, so a failure is a restore rather than a rebuild from nothing. The machine carries Apple’s manufacturer warranty, and repair or replacement runs through Apple’s service process. Our target is to return you to a working system within 30 days.

Your business context lives on your machine. What leaves it depends on the configuration you accept: cloud-first configurations route certain tasks to approved external AI models, and those processing paths are disclosed in the scope before you approve them.

Hatched Stacks does not use your business data to train its own models. When a workflow routes a request to an external provider, that provider’s terms govern the request. Your scope names the approved models and documents each processing path so you can see where data goes before you approve it.

That is what Ultra is designed for: approved workflows running on local models, with workflow-specific data boundaries and documented processing paths. Because local processing has real capacity limits, Ultra begins with workload qualification rather than a fixed machine specification.

You do. Model routing uses customer-owned accounts, so the spending, provider terms, and ability to revoke access stay with your business. Account ownership is written into the accepted scope.

Because one workflow taken properly into production is worth more than five taken halfway. A single workflow gives you a measurable baseline, a clear owner, a safe path to production, and evidence before you expand the system.

The new workflow runs alongside your existing process without replacing it or receiving production authority. It is tested against real conditions while your current process continues untouched, so nothing depends on it until it has earned your approval.

By comparing it with the baseline agreed at the start, such as cycle time, throughput, cost per task, quality, or conversion, and checking it against the acceptance tests. It moves to production only when the workflow owner accepts its controls, exceptions, evidence, and rollback path.

The operating layer includes checkpoints, approvals, and exception handling. Decisions that must remain human-approved are identified during observation and kept that way. Activity records make errors traceable, and defined rollback paths make approved changes reversible.

There is no platform limit on tool connections. Your accepted scope includes the tools required for the workflow being built, and additional tools can be connected as your workflows expand.

The dedicated machine, one workflow taken through the full production process, your organized business context, approved model routing, human approvals, activity records, and recovery documentation. It also includes permissions, spending controls, health checks, logs, backups, and rollback paths.

Yes, and you control them directly. External model usage is billed to your own provider accounts, so you can see and cap that spending rather than paying a hidden margin. Local-model workflows do not incur model-token charges. Electricity, network service, and any approved third-party subscriptions are separate running costs.

No. The next step is a short qualification application, not payment. Final configuration, scope, success measures, and purchasing terms are confirmed after consultation, so you know what is being built before anything is committed. From accepted scope, a typical first workflow is running within 30 days.

Each additional workflow receives its own scope, baseline, and success measures. If you stop working with us, you keep the machine, customer-owned accounts, documentation, and completed workflow. Continuity is defined in the scope so leaving is not a cliff edge.