How Much Does Custom AI Development Cost? A Transparent Breakdown
A custom AI build is priced by scope and risk, not by headcount-hours. Real projects run from about $750 for a scoping teardown to $40,000-$55,000 for a full production integration. A fixed scope protects your budget better than an open-ended hourly or offshore contract, because the estimate and the delivery come from the same person.
The number people quote you says less about the model and more about how they charge. So before you compare prices, understand what actually moves them.
What actually drives the cost
The price of a custom AI project has little to do with how clever the model is. It tracks a handful of honest cost drivers:
How messy your source data is. Clean, structured records are cheap to work with. PDFs, scanned forms, and inconsistent spreadsheets are where the hours go.
How many systems it touches. One workflow inside one tool is a small build. The same workflow wired into Stripe, kintone, Salesforce, and a shared drive of PDFs is a much larger one, because every integration is its own contract and its own failure mode.
Whether a human has to review the output. An AI step that runs unattended is simple. An AI step a person approves needs a review screen, an audit log, and defined failure states, which is real product work.
Demo or production. A prototype that works on a clean sample costs a fraction of something that survives real users, real load, and real edge cases.
Whether you own it at the end. A build that hands over source code, API contracts, and deployment notes carries a little more discipline than a black box you rent forever, and it saves you far more later.
Name those five and you can predict roughly which rung of the ladder you land on.
The price ladder
Here is what the tiers actually cost. These are fixed-scope packages, not hourly estimates that drift.
| Package | Duration | Price | When it fits |
|---|---|---|---|
| AI Workflow Teardown | 3 business days | $750 | You want the single biggest manual bottleneck mapped into a one-page automation plan. Lowest-risk first step, fee credited toward a later sprint. |
| DX Readiness Audit | 1 week | $5,900 | Scope is unclear and you need a process map plus automation plan before building. |
| Quick DX PoC | 2 weeks | $12,500-$18,000 | One narrow workflow automated end-to-end as a working prototype plus demo. |
| MVP Automation Sprint | 4 weeks | $25,000-$35,000 | A usable internal app or workflow with AI integration, deployed for a real pilot. |
| Full DX Integration | 6 weeks | $40,000-$55,000 | Production-ready workflow with multiple system integrations, an admin view, and training. |
| Velocity Retainer | monthly | $9,500-$12,500/mo | Ongoing iteration and roadmap execution after an initial build. |
Most engagements do not start at the top. They start with a small paid step that turns "we think we need AI" into a scoped plan.
Why a fixed scope beats hourly or open-ended
An hourly contract prices the vendor's time. A fixed scope prices your outcome. The difference matters most when something goes wrong, because on an hourly or open-ended deal, the surprises land on your invoice.
Two structural things keep a fixed scope honest. First, no subcontracting: the senior engineer who scopes the work is the one who builds it, so the estimate and the delivery come from the same person instead of drifting apart down a chain of contractors. Second, a defined scope means scope creep shows up as an explicit change, not a silent overrun, which is the whole argument in why fixed-price scope beats scope creep.
A fixed scope also pairs cleanly with a paid first step. A short paid engagement de-risks the big one far better than a free pilot no one is accountable for, which we cover in paid PoC versus free pilot. And if you operate in Japan, DX and AI subsidies can offset a real chunk of the cost, so the net number is often lower than the sticker; the mechanics are in Japan AI and DX subsidies for custom software.
What to ask before you accept a quote
Before you sign anything, get straight answers to four questions:
Does the person who scopes it also build it, or does it get handed to a cheaper team after you sign?
What do you own at the end: source code, API contracts, deployment notes, and tests, or just access to a running instance?
Is the human-review screen inside the price, or is it "phase two"?
What happens if it runs over, and who absorbs the extra time?
If the answers are vague, the quote is vague. A studio that scopes tightly can answer all four in a sentence each. The same discipline shows up in how you brief the work, covered in how to brief a dev studio for an AI PoC.
How Urbano DX prices it
Urbano DX is one senior team, Poland-based and foreign-first, with no subcontracting. Every engagement is a fixed-scope sprint from our packages, and you own everything at handover: source code, API contracts, deployment notes, and tests. No lock-in.
Most clients do not start with a big sprint. They start with the $750 Teardown or the $5,900 Audit to de-risk the decision, then move up the ladder once the scope is real and the number is trustworthy. The proof that this works is a shipped product, not a pitch: in the Buy Houses Japan build, one team built a property web app and the natural-language AI search inside it, on one data model, with one deployment. When you move from a pilot to production, the handover discipline matters as much as the build, which is the point of MVP handover before scale.