A senior pod takes one workflow from a live proof of concept in 3–6 weeks to governed production inside 90 days, deployed in your own cloud account. One accountable owner from scoping to handover. If the metric hasn't moved, the pod keeps building.
Scope a Proof Pod →An AI Pod is a small, senior delivery team assembled around one business workflow rather than one job description. It carries its own accountable lead, its own engineering capacity, and a domain expert from the industry the workflow belongs to, and it is measured against a single business metric agreed before any code is written. Unlike staff augmentation, a pod owns an outcome rather than filling a seat.
The first workflow is the hard one. It absorbs the security review, the integration work, the permissions model and the argument about what "good enough to ship" means. Companies that survive it often stop anyway, because the second workflow means a new procurement cycle and nobody has appetite for another one.
Your first needs proof before commitment. Your fifth needs capacity without a contract negotiation. Most firms sell one motion and make you fit it. The pod ladder exists so that the shape of the engagement changes as the risk does.
You are recruiting for roles you don't yet know how to interview for, against companies paying more, to build a system you can't specify until someone has built one. The pod is the version of that team you can have in three weeks.
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
You own at the end
Working system, architecture decision record, baselined metric — in your cloud.
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:
You own at the end
Code, prompts, evals, runbook — deployed in your cloud account.
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
You own at the end
Every system, every runbook — no platform to migrate off later.
A pod hour is senior delivery time. No junior layer, no bench time, no ramp-up billed against your window.
Fractions are calendar allocation, not accountability. The Pod Lead owns the outcome and the metric for the full window.
Scoped in a call, in writing, before any work starts. Workflow, metric and pod shape agreed in a 30-minute call; commercials in writing before the first line of code.
| Role | What they own |
|---|---|
| Senior Product & AI Lead | Accountability for the outcome and the metric. One owner, start to finish. Not a relationship manager. |
| Delivery / Tech Lead | Architecture, model selection by task and data policy, the value hypothesis, executive alignment. |
| AI Product Engineers | Delivery. Each engineer directs multiple AI agents in parallel; nothing merges unreviewed. |
| Evaluation & QA Engineer | Eval datasets, red-team passes, regression gates, the definition of "good enough to ship". |
| Platform / DevSecOps Engineer | Deployment inside your cloud, SSO, RBAC, private endpoints, secrets, monitoring, cost control. |
| Domain SME (on call) | A retired senior operator from your industry. Sanity-checks the workflow against how the work actually gets done. |
Most pod vendors sell engineers. The SME seat is what catches the four exceptions your brief didn't mention, in week one rather than month three.
| Hiring an AI team | Staff augmentation | Big-firm consulting | OrbitumAI POD Team | |
|---|---|---|---|---|
| Time to first working system | 6–9 months to hire and ramp | Weeks to staff, months to deliver | Weeks of discovery before a build | 3–6 weeks to a live PoC |
| Who is accountable | You | You | A partner who won't build it | One Senior Product & AI Lead |
| What you're paying for | Capacity | Seats | Slideware and a roadmap | A metric that moves |
| Junior layer | Yes, and you manage it | Usually | Yes, billed at leverage | None — senior-only, agent-operated |
| If it doesn't work | Sunk salary | Sunk hours | A phase two proposal | The pod keeps building at no extra fee |
| What you own at the end | Everything, eventually | Fragments | A deck | Code, prompts, evals, runbook — in your cloud |
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Everything runs inside your own account. Private endpoints, your secrets, your network boundary. Nothing leaves your perimeter for us to hold.
SSO and RBAC from day one, not retrofitted after the security review. Full audit trail on every action the system takes.
Code, prompts, evaluation sets and runbooks hand over in full. There is no OrbitumAI platform to migrate off later, and we don't train on your data.
Client names and locations are withheld by policy. The numbers come from delivery records and are stated as measured.
Error rate from 10% to under 1%. Over $100K in annual cost reduction.
Read the full case →60–70% less time spent searching. 40% faster support resolution.
Read the full case →The delivery bench comes out of IIT Bombay, IIM Ahmedabad, BITS Pilani and IIIT Hyderabad and Bangalore, with engineers from Amazon AGI, Bosch and Kearney, and a former YC-startup CTO.
Not proven yet? We keep going at no extra fee.
We define one measurable metric before we write a line of code. If it hasn't moved inside the impact window, the pod keeps building until it does — at no additional fee. You never pay for AI that just sits there.
FAQ
A small senior delivery team built around one business workflow rather than one job description. It has an accountable lead, its own engineering capacity, and a domain expert from your industry, and it is measured against a single business metric agreed before any code is written.
Staff augmentation fills seats you manage. A pod owns an outcome. You brief the workflow and the metric, not the tasks, and the Senior Product & AI Lead is accountable for whether the number moves.
Scoped in a call, in writing, before any work starts. In a 30-minute scoping call we agree the workflow, the metric and the pod shape; you get a written scope and commercials before any work begins. Most first engagements are sized like one senior hire for a quarter, against a system that ships in weeks rather than a role you're still recruiting for in six months.
A live proof of concept in 3–6 weeks. Governed production inside 90 days, assuming your security review runs in parallel rather than after.
Yes, and that is the default. AWS, Azure or GCP, inside your network boundary, behind your SSO, under your audit trail.
Code, prompts, evaluation sets, runbooks and the deployed system. All of it, in your account. Nothing of ours is required for it to keep running.
