A standing engineering capability inside your team, for the year after the build when the interesting problems start.
Price
$18k to $32k per month
Duration
Three month minimum, then rolling
How it is priced
Minimum three months, then rolling with 30 days notice. The range moves on the shape of the pod and whether on-call participation is included.
Who is on it
A named delivery lead and named senior engineers. The same people month to month, in your standups, on your board, in your review queue.
Written for
Post Series B SaaS and enterprise teams running AI in production who need capacity that already knows the system rather than capacity that has to learn it.
The month after launch is when the real work starts: a provider changes behaviour, retrieval quality quietly decays as the corpus grows, costs drift, and a customer finds an edge case nobody modelled. A pod exists for that year. It is not a body shop and it is not a support desk. It is the same named engineers who know why the system is shaped the way it is, working on your board, at your pace.
Stated here rather than discovered in month three. Anything on this list can be scoped separately, and we will say what it would take.
One call with the people who know the problem, then a written brief back to you within two working days: what we understood, what we think the hard part is, what is explicitly out of scope, and which of the four engagements fits. If none of them fits we say that instead of reshaping your problem to match a price list.
Output: A written brief and a named engagement, or an honest noBefore any prompt is written we build a labelled set from your real examples with your domain experts, split by category, with a held back portion. The pass threshold goes in writing, with the consequence of missing it agreed at the same time. This is the week that makes every later argument about quality a number rather than an opinion.
Output: A labelled evaluation set, a harness, and an agreed thresholdOne path through the system, end to end, running in your cloud account, usually inside the second week. Not a prototype on a laptop. Deploying early is how integration risk, credential problems and data access surprises surface while there is still time to change the plan.
Output: A deployed slice on your infrastructure and a working pipelineEvery week ends with a working demonstration against the evaluation set rather than a status document. You see the score, the failures, and what we are doing about them. Anything at risk is raised in the week it becomes at risk, not in the week it becomes a problem.
Output: Shipped increments, a score per week, and a visible risk listGuardrails on the output path, escalation payloads, tracing, cost and latency instrumentation, alerts wired to people who can act, and runbooks for the two or three ways this specific system fails. Where the system can act, it shadow runs against live traffic before it is granted authority.
Output: Guardrails, dashboards, alerts, runbooks and shadow run resultsYour engineers make the last change while we are still there to watch. Repository, infrastructure as code, evaluation suite, documentation and access all sit with you, and none of it depends on an account we control. If you want us to stay, that is an Embedded AI Pod with its own scope, not a dependency we engineered into the build.
Output: Code, IP, docs, evaluation coverage and a team that can run itA pod is bought as a capability with a lead accountable for outcomes, a monthly written report, and a defined evaluation and monitoring remit that runs whether or not there is a feature in flight. It is not billed per person per hour and it is not managed by you as individuals.
The team is based in India. There is a live overlap with United States mornings on the east coast and a full overlap with Australia and the Gulf, and the rest of the day runs as written async handoffs. In practice that means work continues after your team logs off, and the handover note is waiting when they log back on.
Yes, and the first month is deliberately shaped as an onboarding: reading the system, running the evaluation suite if there is one and building one if there is not, and producing a written assessment of what is fragile. You get that assessment whether or not you continue.
Thirty days notice after the third month. Documentation and evaluation coverage are contractual deliverables rather than best efforts, so the exit is a handover rather than an excavation.
engineering / the other three
You get a written view of the problem within one working day, from an engineer, including the version where the answer is that this is not a build.