For startups and small businesses already generating revenue who want AI working inside what they run — a product, a new feature, or an operation that's eating your team's time. We scope it, build it, and ship it: prove it on real data, put it in front of real users, then scale.
Best for teams with real customers & revenue — typically $2M+.
New capabilities inside what your customers already use — search, agents, automation, insights.
From concept to launched — a standalone product or a new AI-powered line inside your business.
Support, documents, data, ops — an AI system your team runs on and actually relies on.
↑ Product, feature, or operation — this is what makes you more than a "startup product studio."
Whether it's a new build or AI added to something you already run — each build is scoped in writing before we start, with one metric agreed before we write a line of code.
AI Pods
Senior leadership stays on the workflow with you. Delivery capacity scales with its complexity. Every pod ships into your own cloud account and is measured against one business metric agreed before the first line of code.
To a live proof of concept
400 pod hours / month
Validate and launch one bounded, high-value AI workflow.
Best for: your first AI system, or rescuing a pilot that stalled between demo and deployment.
Your pod
To governed production
800 pod hours / month
Own one production workflow from discovery through adoption.
Best for: a proven use case that has to survive a security review and a real user base.
Your podEverything in a Proof Pod, plus:
Ongoing capacity, set to the roadmap
1,600 pod hours / month
Run two AI workstreams with shared senior leadership.
Best for: teams past their first workflow who don't want a new procurement cycle each time.
Your pod
Concrete deliverables, not "AI consulting." One use case — built or integrated, taken to production, and handed to your team.
We define one measurable metric before we write a line of code. If it hasn't moved within the impact window, we keep tuning until it does — at no additional cost. You never pay for AI that just sits there.
So the scope stays clear — and everyone knows the line before we start.
Included — one end-to-end use case (e.g. "add an AI assistant to our product's help section," or "auto-process inbound invoices") with up to 2 integrations and one round of tuning.
Separate build — a second unrelated use case, extra integrations, or ongoing feature work rolls into SHIP or a monthly plan.
↑ Protects your margin and stops scope creep.
FAQ
It's built for teams already generating revenue — typically past $2M — with real customers and a workflow worth automating. If you're pre-revenue and still testing the idea, a pod is the wrong instrument and we'll say so on the call rather than sell you one.
Scoped in a call, in writing, before any work starts. We agree the workflow, the metric and the pod shape in 30 minutes and send written commercials. Nothing begins until you've seen the scope and the number in writing.
One workflow live on your real data, with your real users, in 3 to 6 weeks. Not a demo on sample data — the actual thing, running, with the metric baselined so you can tell whether it worked.
The code, the prompts, the evaluation datasets and the runbook, in your repository. It runs in your own cloud account. There's no platform of ours in the path and nothing to migrate off if you stop working with us.
