Insights
By Ege Engin Özdaş (Co-Founder & CEO), Şener Özer (Co-Founder & CTO) & Gökçe Özyurt (Co-Founder & CPO) — Staterics · Published 2026-08-03 · Updated 2026-08-03 · 11 min read
The short answer: AI implementation cost runs $10,000–$500,000 as a one-off project across the agency guides ranking for this question; Clutch data reported by Uptech puts a typical project at $10,000–$49,000. Staterics prices it monthly instead: a platform fee from $750 per month plus AI usage metered in RIC Tokens at $0.16–$0.25 per token, no development cost.
How much does AI implementation cost? At Staterics, two published lines: a platform fee from $750 per month, depending on system complexity and number of users, plus AI usage metered in RIC Tokens at $0.16–$0.25 per token. There is no development cost, and recurring billing starts the day your system goes live, not the day you sign.
That is a published number, and almost nobody publishes one. The pages ranking for this question are written by the agencies selling the work: Coherent Solutions, Future Processing, InData Labs, Uptech. None of them ends in a price. This one does, and it also covers what moves that price, the costs the quotes leave out, and the cases where you should not buy at all.
Search this question and you will find long, detailed guides from AI agencies — cost-factor lists, budget percentages, industry tables. Read any of them to the end and the number never comes. Reviewed in August 2026, the ranking pages from Coherent Solutions, Future Processing, InData Labs and Walturn all stop at ranges: roughly $10,000 at the small end, $500,000 and beyond at the enterprise end. The real figure arrives later, on a sales call, after the quote has been shaped to your budget.
The one figure with a survey behind it comes from outside the agencies: Clutch’s survey of development firms, reported by Uptech, puts a typical AI project at $10,000–$49,000. Even that is a five-fold spread. When every project is scoped from scratch, the range can stay wide, and wide ranges favor the seller. A published number does the opposite. It is the same in every country, and everything that moves it has to be written down, which is what the rest of this page does.
If a vendor won’t publish a price, the price is whatever they think you’ll pay.
The guides answer this with budget percentages: data is “15–25% of cost,” compliance “adds 5–10%.” Even where that is true, you cannot act on it. Here is what actually moves the price of an AI operating system, in plain terms:
An AI employee that answers calls and books into one calendar is a smaller build than one wired into your phones, your stock, your invoicing, and your reporting. Every connection is real work, done once, and it is also the reason the system can act instead of just answer.
If your prices, policies, and customer history live in a few clean places, handover is fast. If they live in seven spreadsheets and one manager’s head, part of the build is gathering them. That is effort, and it moves the price.
A system that drafts replies for your team to approve is a smaller build than one trusted to book, confirm, and chase on its own. Wider authority means more rules to map and more testing before go-live. That is where the complexity actually sits.
More users and more locations mean more interfaces, more routing, and more reporting views. The platform fee scales with the number of users — stated up front, not discovered on an invoice.
Notice what is not on the list: your industry. Healthcare, retail, logistics: the label changes the rules a build has to map, not the price logic. What you pay tracks the complexity of your operation, not the sector it sits in.
Even the honest project quotes cover only the build. Three costs sit outside almost every project quote, and none of them is small:
None of those disappear — anyone who says otherwise is selling. The first can be cut to one defined step, data handover, with the 14-day clock starting only when it is complete. The second is a running cost under every model, so the question to put to any vendor is whether it is metered somewhere you can see it. The third has to be designed for: a system that reports to the owner on its own is the one that does not get abandoned.
Some operations should not be sold an AI system, and the cheapest project is the one you do not start. Check the work against three things before you spend anything:
Order matters too. If your data is scattered across seven places and nobody trusts the numbers, the fix starts there, not with a purchase. A system built on records the business already disputes will produce answers the business disputes, faster and at scale.
Almost every ranking guide prices AI as a construction project: pay to build it, then pay to maintain it. A monthly operating system prices it as a service instead. The two, side by side:
| A one-off AI build | An AI operating system, monthly |
|---|---|
| The guides quote $10,000 to $500,000 or more — paid before the system has done a day of work. | No development cost. A platform fee from $750/month plus AI usage in RIC Tokens at $0.16–$0.25 per token, both starting at go-live. |
| Maintenance is a separate contract, negotiated after you already depend on the system. | Running, monitoring, and improving the system is the service. Same bill. |
| Months of development before anything works. | AI employees live within 14 days of data handover; the complete system within 90 days. |
| The code is yours at the end. So is the hosting, the monitoring, and every future change request, quoted separately. | If you ever leave, everything the system accumulated is handed back to you. The record is yours. |
Run it with real numbers. Twenty-four months of the monthly model comes to about $21,500: the $750 platform fee plus, say, 600 RIC Tokens a month, which prices at $147 on the $0.25 and $0.22 tiers. AI employees are live in the first two weeks and the system is maintained throughout. A $40,000 build has spent more than that before it answers its first call, and the maintenance contract starts after. The build only wins if it outlives the comparison by years.
The published numbers, in one place. Your bill has exactly two lines. Line one is the platform fee: from $750 per month, scaling with system complexity and number of users. Line two is AI usage, metered in RIC Tokens at $0.16–$0.25 per token, tiered by monthly volume. A monthly model absorbs the run cost that project quotes leave out: running the system is the service, and AI usage is metered on a published rate card, visible on every invoice. The full rate table is in the next section.
Recurring billing starts at go-live: you are never charged a monthly fee for a system that is not running, and there is no development cost either way. The annual lane works differently. It takes a deposit up front, and if delivery runs past day 90 you choose — 100% of the deposit back, or pay the balance only on delivery.
The pricing is also consistent globally: the number does not change based on what a salesperson thinks your market can bear. Capacity is capped at ten new builds a month, which is how the 14-day and 90-day clocks stay commitments we can keep.
You should not pay a monthly fee for a system that isn’t running yet.
Every AI action on the platform is metered in one unit, the RIC Token: a call answered, a message replied to, a document read. Voice and text share the same meter, and each slice of your monthly usage is priced at its own rate, like tax brackets. The more your AI does, the cheaper every additional token gets, automatically. The rate card:
Voice and text share one meter — every call moves your messages into a cheaper tier.
One term is worth reading before you sign with anyone, including us: our token rates can be revised with 30 days’ written notice if the underlying model provider pricing changes materially. Those provider list prices are public and they do move. Every AI vendor carries that exposure; most bury it. Ours is in writing — ask every vendor where theirs is.
Consumption is steady enough to estimate before you sign. What each kind of interaction typically uses:
Billing is metered on real usage. An unusually long call pays for exactly what it consumed, never a rounded-up flat fee.
Two worked examples. A text-focused clinic running around 300 chat messages and a handful of documents, about 80 tokens, pays about $20 in AI usage. A 24/7 voice reception handling around 3,000 call minutes, about 3,000 tokens, pays $655 — an effective rate of about 22 cents per minute. Usage is billed monthly in arrears, as a separate line beside the platform fee, and the meter resets to the first tier each month.
The published price answers “from what?” Your exact number depends on the four factors above. The fastest way to get it is the free Operations X-Ray: forty-five minutes on how your business actually runs, and you leave with a friction map — what manual work costs you each month, and the top three workflows an AI system would remove first. The map is yours to keep, whatever you decide.
You can narrow the band before that call. Count the systems the AI would have to touch: phones, calendar, stock, invoicing, reporting. Count the places your prices and policies actually live today. Decide which of those decisions it may make without a person in the loop, and how many users and locations it has to serve. Four answers, and you already know which end of the range you sit at; the X-Ray confirms it against how the business really runs.
The same published model as for a large one: from $750 per month depending on system complexity and number of users, plus AI usage metered in RIC Tokens at $0.16–$0.25 per token, tiered by monthly volume. We build for any size of business, from a single location to an enterprise, and the pricing logic does not change with the label.
At Staterics, two lines: a platform fee from $750 per month, plus AI usage metered in RIC Tokens at $0.16–$0.25 per token depending on monthly volume. What moves the platform fee: how many systems the AI connects to, where your data lives, how much the AI may decide on its own, and how many users and locations it serves.
In RIC Tokens — one unit across voice and text. A voice-call minute is about 1 token, a chat message about 0.25, a document of roughly 20 pages about 0.75. Tokens are priced in monthly volume brackets from $0.25 down to $0.16, billed monthly in arrears as a separate line beside the platform fee, and the meter resets each month.
No. There is no development cost in Staterics builds. You pay the platform fee and metered token usage once the system is live.
Because most AI is sold as scoped projects, where a wide range leaves room to shape the quote on a sales call: $10,000 to $500,000 in the agency guides ranking for this query. Published pricing removes that room, which is why so few publish one.
Four things, in our builds: the number of systems the AI connects to, how scattered your data is at handover, how much the AI is authorized to decide without a person, and the number of users and locations. Industry labels do not change the price logic.
We do not publish ROI promises — that number belongs to your operation, not our marketing. What can be measured is the other side: the free Operations X-Ray maps what manual work currently costs you each month, so the comparison against from $750 per month plus your RIC Token usage at $0.16–$0.25 per token is yours to make with real figures.
Not the platform fee — it starts the day your system goes live, paused rather than deferred, with no back-pay at delivery. What you do pay during the build is AI usage: the RIC Tokens your system consumes while being trained and tested, billed as used. The annual lane takes a deposit up front, with an objective guarantee: if delivery runs past day 90, you choose — 100% of your deposit back, or pay the balance only on delivery.
When the work does not repeat, when nobody inside the business will own the system, or when a wrong answer would be irreversible and no human check fits the workflow. If any of those describe your operation, we will say so at the X-Ray — a build that fails serves nobody.