Customer-controlled infrastructure
A dedicated Apple silicon operating anchor with access, accounts, documentation, continuity, and support boundaries defined in the accepted scope.
AI systems built around the way your team works
Connect business context, approved models, authorized tools, and specialized agents on a dedicated Apple silicon machine your business controls.
A different kind of AI company
Bring context to the surface with content-aware recommendations grounded in your operational data, then act on them safely to generate real results for your business.
One connected operating layer
Build around the business you already operate, then expand one accepted workflow at a time.
A dedicated Apple silicon operating anchor with access, accounts, documentation, continuity, and support boundaries defined in the accepted scope.
Organize the offers, customers, policies, operating knowledge, data structures, and approval rules relevant to the first workflow.
Coordinate approved models, tools, agent roles, handoffs, checkpoints, exceptions, and activity records instead of isolated prompts.
Consequential actions remain bounded by permissions, acceptance tests, human review, spending controls, and rollback paths.
Focus the system where work happens
Begin with one recurring process, prove it against a real baseline, and expand only after acceptance.
Lead research, CRM enrichment, follow-up preparation, funnel analysis, and exception routing.
Human approval and acceptance criteria defined by workflowCampaign briefs, content generation, channel adaptation, publication preparation, and performance summaries.
Human approval and acceptance criteria defined by workflowData processing, process monitoring, handoff coordination, quality checks, and operating documentation.
Human approval and acceptance criteria defined by workflowWebsites, applications, specifications, testing, release preparation, and internal system improvements.
Human approval and acceptance criteria defined by workflowFrom existing process to production
When a 30-day target is appropriate, the baseline, tests, responsibilities, dependencies, and acceptance criteria are defined before work begins.
Choose one recurring workflow, document its owner and operating context, and capture a measurable baseline.
Configure the machine, business knowledge, models, integrations, agent roles, approvals, and exceptions.
Compare cycle time, throughput, cost per task, quality, or conversion without silently replacing the existing process.
Put the workflow into production only after its tests, controls, evidence, responsibilities, and rollback path are accepted.
Operate with boundaries and evidence
Customer-controlled infrastructure, disclosed model routing, workflow-specific data boundaries, human approval, and auditable activity create a more accountable operating model.
Completely local processing is available for qualified workflows through a workload-selected Hatched Ultra architecture.
Hatched Launch Stack
Start with the Launch Stack and one carefully scoped production workflow. Capacity upgrades and completely local options are compared on the pricing page after the initial overview.
View the starting offerFinal configuration, scope, timing, access, tests, support, and acceptance are confirmed after consultation. Model usage, subscriptions, advertising, and ongoing maintenance are separate unless included in writing.
Public proof records will be added only after the work is complete, its before-and-after measurements are verified, and publication permission is obtained. Until then, targets remain targets—not testimonials.
Built with Dawson
Commission a connected AI operating foundation designed around the way your business actually works.
Hatch Your Stack