Artificial Intelligence Development Services: What You Actually Get

Key numbers

• Builder Pod $5,000/month, Growth Pod $10,000/month, Enterprise custom, all month-to-month with 30 days' cancellation notice
• A pod is typically working within five business days of signing, with first shipped code in week one or two
• Two HIPAA-aligned platforms shipped: a compounding-pharmacy network (seven-year immutable audit log, 490+ unit tests) and a Medicare/Medicaid billing-audit dashboard
• An air-gapped fraud-audit engine ran eight detectors across 58 modeled counties with zero external network calls
• A political-data platform scored 25.3 million voters and matched $2.365 billion in federal contributions across three states on one codebase

What "AI development services" actually means

The phrase gets used to describe three very different things: a consulting deck that recommends an AI strategy, a fixed-price project with a deliverables list and change orders, or a team that writes and ships code every week until the system works. We do the third one.

Concretely, "AI development services" at our shop means a dedicated pod, a pod lead plus a bench of senior engineers and QA, working inside your existing tools on your existing infrastructure. There is no separate "AI team" handing off to an "implementation team." The people who scope the build are the people who write it, and the code lands in a pull request in your repository, reviewed by the named engineer who owns it, with typed contracts and tests running in CI.

That distinction matters more than it sounds like it should. A lot of AI vendor engagements produce a strategy document, a proof-of-concept in a sandbox nobody can deploy, or a demo that never touches production data. What we ship is the opposite: production code, in your cloud account, from the first week.

How the engagement actually works, step by step

The process is the same whether the build is a voice-to-chart clinical tool, a fraud-detection engine, or an internal ops dashboard. It runs in five stages, and none of them involve a sales deck.

1. Scoping call. A single working session, roughly 30 minutes, where we map the problem to a rough scope, a price tier, and a start date. No discovery workshop series, no six-week requirements phase.
2. Free prototype. We build a clickable prototype of the core flow and hand it over. You are committed to nothing after this. If you walk away, you keep the prototype.
3. Pod deployment. If you approve the build, a pod, a lead plus two to five senior engineers and QA depending on tier, is typically working within five business days. First shipped, tested code usually lands in week one or two, not month three.
4. Weekly shipping. Daily standups happen in your existing channel (Slack, Teams, whatever you already use). Code ships weekly into your repository and your cloud account or VPC, with async updates between calls.
5. Handover. Whenever the engagement ends, whether that is at project completion or a 30-day cancellation notice, you receive the repository, migrations, deploy pipeline, and documentation. Nothing is withheld.

You can read the mechanics in more detail on how the engagement works, and see how pods are staffed and structured on the pods page.

Here is the same flow as a diagram:

Loop repeats weekly: daily standups in your channel, code ships every week, until the pod is paused or ends.

What it costs: the three tiers

Pricing is published and fixed. There is no per-hour billing, no statement of work with change orders once a pod starts, and no hidden ramp fee. You pay a monthly rate for capacity, and you can pause or cancel with 30 days' notice by email; a paused month is not billed, and your seat is held.

Tier	Price	Build tracks	Team	Cadence
Builder Pod	$5,000/month	1 active build track	Pod lead + 2-engineer bench	Weekly ship, async updates, sprint roadmap
Growth Pod	$10,000/month	2 concurrent build tracks	Pod lead + 3-engineer bench	Weekly ship, bi-weekly strategy call, architecture planning
Enterprise Organization Pod	Custom	3+ parallel build tracks	Dedicated senior lead + 3-8 engineers	Weekly ship, executive roadmap reviews, priority SLA

All three are month-to-month. The Growth Pod adds a hosting discount and priority support; the Enterprise tier includes hosting outright and adds architecture ownership plus internal tooling builds across departments. Full details and current terms live on the pricing page.

Because the reference material behind this article does not include sourced third-party benchmarks for competitor pricing or labor-market salary data, we are not going to assert a specific dollar comparison here. If you want that framing, our AI development cost breakdown and our hire vs. pod comparison for AI engineers work through the tradeoffs with the numbers we can actually stand behind. What we can say plainly: a Builder Pod is one fixed monthly line item that replaces the multi-month cycle of writing a job description, screening, interviewing, and onboarding a senior engineer, and it can be canceled with 30 days' notice if the work stops.

Who owns the code, the data, and the IP

This is the term that decides whether a vendor relationship is actually safe to enter, and it is worth being specific about.

Everything ships into your own repository and your own cloud account or VPC starting in the first week. You own all code, data, models, and IP from day one. There is no license-back clause, no requirement to keep paying to keep using what was built, and nothing in the system calls a proprietary service that only exists on our side. If we disappeared tomorrow, the system keeps running exactly as it did the day before.

That is different from a lot of "AI platform" vendors, where the product you get is a configuration on top of someone else's hosted service, and your access ends when the contract does. It is also different from a consultancy that delivers a final zip file at the end of a fixed-bid project, where the code was written against assumptions nobody documented. Handover here means the repository, the migrations, the deploy pipeline, and the documentation, on the day you ask for it, not the day the contract legally requires it.

The compliance posture: SOC 2, BAAs, and HIPAA-aligned controls

If you operate in a regulated domain, the compliance question usually comes before the pricing question, and it deserves a direct answer.

A SOC 2 Type II report is available under NDA on request. Business Associate Agreements are signed on request for any build that touches protected health information. Work follows HIPAA-aligned controls: access logging, encryption at rest and in transit, role-based access control, and audit trails built into the schema, not bolted on after a finding.

Here is the honest caveat that a lot of vendors skip: there is no such thing as "HIPAA certified." HIPAA does not issue certifications to vendors or software. The correct, and only honest, claim is a signed BAA plus HIPAA-aligned controls. Any vendor who tells you they are "HIPAA certified" is either using loose language or does not understand the regulation. Full detail on what this covers and does not cover is on the security page, and if you want the deeper version of this argument, we wrote a longer piece on what HIPAA-compliant software actually requires.

Two platforms we have shipped operate under exactly this posture. A compounding-pharmacy network's platform runs clinic, patient, and platform-admin portals on one design system, with a seven-year immutable audit log, dual prescriber paths, consent and e-sign flows, and 490+ unit tests, with patient-facing screens passing WCAG 2.1 AA. A separate build is a Medicare/Medicaid medical-billing audit dashboard, built with the same HIPAA-aligned controls applied to claims data instead of patient charts.

What we have actually shipped (evidence, not promises)

It is easy for any vendor to claim they can build "AI-powered" software. The more useful question is what has actually gone into production, with what specs, and under what constraints. Three builds are worth naming in detail because they cover the harder end of the spectrum: regulated data, air-gapped environments, and scale.

A compounding-pharmacy network. The challenge was routing that cannot fail silently: a missed prescription-routing failover, or a gap in the audit trail, is a compliance liability, not a bug ticket. We built a HIPAA-grade SaaS platform across clinic, patient, and platform-admin surfaces, spec-first, with every phase checked against numbered requirements before it merged. Eleven epics shipped behind that spec gate, 490+ unit tests passing, strict TypeScript typecheck green, and patient-facing screens meeting WCAG 2.1 AA. If you want the build walkthrough, see how we built HIPAA-grade pharmacy routing with a seven-year audit log.

A public-sector spend auditor. The constraint here was that sensitive financial data could not leave the building. We built a vendor-spend audit engine that runs fully offline, air-gapped, with local models making zero external calls. Eight fraud detectors run over an ingest, enrich, detect, score pipeline, modeled across 58 counties, with a dashboard that drills from a jurisdiction summary down to a single flagged payment, and per-jurisdiction PDF briefings generated automatically. This system is designed to surface duplicate payments, contract-splitting, and shell-vendor patterns; it was validated on modeled data, not presented as having recovered real public funds. The full pipeline is documented in building an air-gapped fraud detection pipeline.

A political data and campaign-intelligence firm. The challenge was scale, not novelty: raw statewide voter files and federal contribution records with no way to turn tens of millions of rows into something a campaign could act on. We built a unified voter-and-donor graph with ML turnout and persuasion scores per voter, federal contributions matched back to individuals, and choropleth district maps, with new states onboarding through a single command that profiles, scores, and verifies the data before it goes live. The platform now runs 25.3 million voters, 250.9 million vote-history rows, and $2.365 billion in matched federal contributions across three states on one codebase, each gated by an automated end-to-end verifier. The pipeline mechanics are in scoring 25 million voter records.

None of these were built from a template. Each started as the same scoping call, the same free prototype, and the same weekly-ship pod. A fuller sample of shipped work is on the projects page.

Team composition and how fast it actually moves

A pod is not one contractor with an OpenAI subscription. The composition scales with tier: a Builder Pod is a pod lead plus a two-engineer bench; a Growth Pod adds a third engineer and bi-weekly architecture and strategy calls; the Enterprise Organization Pod puts a dedicated senior lead over three to eight engineers running parallel build tracks across departments. QA is part of every tier, not an add-on.

Speed comes from removing the parts of a traditional hire that take months: writing a job description, screening resumes, running interview loops, negotiating an offer, and then a multi-week ramp before the new hire ships anything real. A pod skips all of that. Deployment is typically within five business days of signing, and the first shipped, tested code usually lands in week one or two. The team works across US Pacific hours and Central European time, so a morning kickoff on the US side often lands on work that was already written and tested overnight.

When a pod fits, and when it does not

A subscription pod is the right shape for a specific set of problems, and wrong for others. Being honest about the mismatch cases matters more than the pitch for the fit cases.

A pod fits when:

• You need production code shipping in weeks, not a strategy deck in a quarter
• The build touches regulated or sensitive data and the vendor needs to prove compliance posture in writing, not just claim it
• You need senior engineering capacity now, and a 3-6 month hiring cycle is not an option
• The scope will keep evolving after the first release, and you want month-to-month flexibility instead of a fixed-bid contract with change orders
• You want the code and the IP to be unambiguously yours from the first commit

A pod does not fit when:

• You need a single, purely advisory engagement with no code shipped, in which case a fractional CTO engagement is the better shape
• The work is a one-off, sub-month task better suited to a single contractor than a full team
• You need on-site, in-person staff for reasons unrelated to the software itself
• The organization is not ready to grant repository and cloud access in week one, since that access is how the model works

If you are still deciding between a pod and hiring in-house, build pod vs. in-house hire works through that decision in more depth, and custom AI development covers the broader category this article sits inside.

A checklist before you sign anything

Before committing to any AI development vendor, pod-based or otherwise, get direct answers to these:

1. Does the code ship into our repository and our cloud account from week one, or does it live in the vendor's environment?
2. Is there a license-back clause, or do we own the code, data, and models outright?
3. What happens to the system if we cancel: do we get the repository, migrations, deploy pipeline, and documentation immediately?
4. If our data is regulated, will the vendor sign a BAA, and can they describe their controls in specific terms rather than the word "compliant" alone?
5. Is pricing a fixed monthly rate with a plain cancellation notice, or is there a per-hour rate, a change-order process, or a multi-month minimum term?
6. What is actually shipped in the first two weeks, and can they show a comparable build they have shipped before?

The short version

AI development services, done the way we run them, is a scoping call, a free prototype you keep either way, and then a monthly pod, $5,000 for a Builder Pod, $10,000 for a Growth Pod, custom for Enterprise, that ships tested code into your own repository every week. You own the code, data, and IP outright with no license-back, compliance posture is documented (SOC 2 Type II under NDA, signed BAAs, HIPAA-aligned controls, never "HIPAA certified," because that certification does not exist), and the evidence is production builds you can check against stated specs rather than a pitch deck. If a vendor cannot answer the ownership, cancellation, and compliance questions in the checklist above in plain terms, that is the answer you need before the price ever comes up.