AI consulting cost for specialty manufacturers.
AI consulting for mid-market specialty manufacturers ($10M to $100M revenue, our typical range) costs from $10,000 as a fixed-fee custom commission. The fee covers diagnosis. prototype. a 4-to-6-week production build. integration with the manufacturer's ERP (enterprise resource planning system; JobBOSS. Epicor. Global Shop Solutions. IQMS). MES (manufacturing execution system. tracks shop-floor work). and QMS (quality management system).
A commission is not the right path for manufacturers with fewer than 20 employees (SaaS economics win), shops whose only need is machine monitoring (sensor platforms cover that), or shops without a named quoting or scheduling constraint worth automating. The deciding factor is whether the manufacturer has a workflow gap between ERP (the system that runs finance, inventory and orders) and shop floor that generic products cannot close.
For owners and operations managers weighing automation investment against quoting and scheduling bottlenecks.
Key Terms
Quote-to-cash cycle: the elapsed time from customer inquiry to payment receipt; AI can compress this cycle by automating estimating, routing, and invoicing steps that manual processes stretch across days or weeks. Work-order routing: assigning production jobs to machines and operators based on capacity, capability, and material availability; a scheduling problem where AI outperforms static rules. First-pass yield: the percentage of parts that pass quality inspection without rework; AI-driven process monitoring can identify drift before it produces scrap. ERP-to-shop-floor gap: the disconnect between what the ERP system plans and what actually happens on the production floor; custom AI bridges this gap by integrating real-time machine data with ERP scheduling logic.
See the fee band on the pricing page.
Custom commission, manufacturing SaaS, Big Four engagement, and internal hire compared.
The commission fee is paid in two installments: one at production-build start (after the prototype works), one at handoff when the operator receives code, prompts, models, and datasets. There is no proprietary runtime to license and no consumption-based pricing.
Off-the-shelf AI products serving manufacturers typically price per-user per-month. For a mid-market operator in this band, the perpetual subscription compounds rapidly. Within 18 to 24 months of handoff, the math on a custom commission typically beats the math on a comparable SaaS (software you rent by subscription) subscription.
Big Four AI consulting (Deloitte, Accenture, McKinsey, PwC) runs an estimated $400,000 to $1.4 million for strategy plus a separate $1 million-plus implementation (estimate), calibrated for enterprises at roughly $500 million or more in revenue (an estimate), not mid-market.
Internal AI hires fully-loaded cost an estimated $50,000 to $350,000 per year, plus six to twelve months of build-out before the first system ships. Most shops run both: the commission ships in 6 to 7 weeks, the hire owns the next year.
The $499 AI-Ready Audit (our published price) is the fastest way to see which path fits; start at colabcontent.com/ai-ready-audit/.
The bands above are the specialty manufacturers version of one pricing model. The cross-industry view of custom AI development cost for mid-market businesses shows how the same fixed-fee commission is scoped in the other four verticals, and what moves a project from the bottom of a band to the top.
What is included in a fixed-fee commission for manufacturers.
The fixed-fee commission for manufacturers includes the audit call, the 7-to-10-day working prototype (based on past commissions) on the operator's real data, and typically a 6-to-7-week production build (based on past commissions), integration with Epicor Kinetic, JobBOSS, Global Shop Solutions, IQMS as needed, handoff of code, prompts, models, datasets, and runbook (the written operating instructions), and optional care after handoff at $997 a month, cancellable on 30 days notice.
Not included: third-party API (application programming interface) costs the operator chooses to incur (LLM, large language model, provider fees; cloud compute; integration vendor charges), and any work outside the diagnosed constraint. Scope expansions are renegotiated transparently.
Operator data stays inside the operator's own cloud tenant (a private cloud account) under NDA (a signed non-disclosure agreement). ColabContent does not retain operator data or commissioned system components after handoff.
See the full breakdown on the pricing page.
How manufacturers commission costs compare to SaaS subscriptions.
For manufacturers considering off-the-shelf AI SaaS products, the headline subscription cost typically represents 20 to 40 percent of true first-year cost. Data preparation runs 20 to 30 percent of implementation cost. Consumption-based pricing (documents processed, queries run) creates unexpected charges; 78 percent of IT leaders in a recent survey reported surprise costs from consumption-pricing models.
A custom commission is one-time fixed fee with no consumption-pricing surprises, no per-seat scale-up cost, and code owned at handoff. The trade-off is up-front cost (one fixed fee from $10,000) versus ongoing SaaS subscription. For operators with a five-to-ten-year horizon on the workflow, the math favors the commission.
Pricing decisions ultimately come down to whether the operator's leading constraint is addressable by a custom build at the fee band above; the audit call surfaces that answer.
Two installments, fixed in advance.
Installment one is paid at production-build start, after the prototype works. The amount is approximately half the total fee. The trigger is the operator's explicit decision to proceed to the production build, based on the prototype's demonstrated performance against the target written down after the audit.
Installment two is paid at handoff, when the operator receives code, prompts, models, datasets, runbook, and integration documentation. The system is functioning in the operator's own cloud tenant at this point. Optional care after handoff is $997 a month and cancels on 30 days notice.
There is no retainer fee, no perpetual SaaS subscription, no per-user charge, and no proprietary runtime to license. The operator owns the system at handoff and is free to take it in-house or to another vendor for future evolution.
When commissioned AI typically pays back at a manufacturer.
Most mid-market operators in this vertical see positive ROI on a commissioned AI build within two to four quarters post-handoff. The faster windows tend to be high-velocity workflows (quote turnaround, COI processing, call routing). Slower windows tend to be capacity-recovery workflows where the dollar value compounds over the second year.
This is post-handoff measurement from production, not projected or pilot-stage numbers.
Operators bring their own leakage measurement to the audit call. The audit call writes the constraint in a sentence and surfaces the rough dollar leakage. If the math does not work, ColabContent says so and the engagement does not proceed; we turn away qualified prospects rather than commission a build that will not pay back.
Related pages for manufacturers.
See the best AI consultants for manufacturers guide for ranked comparisons against off-the-shelf products. See the AI for manufacturers hub for the vertical landing. The pricing page documents ColabContent's engagement model across all five verticals.
Order the $499 AI-Ready Audit to walk through the math for your specific operation. The call ends with the constraint written in a sentence and an honest assessment of whether a custom commission is the right buying motion.
How to decide whether a commission is the right next step.
Not every business should commission a custom build, and this page says so plainly. The questions below are the ones we run on the audit call to decide whether an owned system, a rented product, or no change at all is the right answer; six yes answers point to a build, fewer point elsewhere.
The four-question sequence operators run before booking.
Operators who arrive at the audit call having run the sequence usually commission the build that same week. The sequence asks four questions in a specific order. First, is the leading constraint actually addressable with AI, or is it a process problem, a staffing problem, or a stack problem that AI would not solve. Second, if AI is the right intervention, is the right buying motion a custom commission, an off-the-shelf product, or an internal hire. Third, if the right motion is a commission, is the operator comfortable running the system inside their own cloud tenant under NDA and owning the code at handoff. Fourth, is the budget for a custom build from $10,000 real this quarter.
Operators who answer yes to all four book the call. Operators who answer no to any one of them either change the question (the leading constraint is different, the budget moves, the cloud posture changes) or take a different path. We do not push operators who land at a "no" on any of the four into a commission they will not be served by.
The three signals operators watch for after handoff.
Twelve months post-handoff, three signals tell the operator whether the commission performed against the target written down after the audit. First, the dollar or hour delta on the workflow the commission addressed, measured against the pre-engagement baseline. Second, the percentage of the workflow the AI layer now handles autonomously versus the percentage that still routes to a human reviewer. Third, the number of times the operator's team has modified the build's prompts, models, or integration code on their own without ColabContent involvement. All three should be improving over time. If they are not, the optional small post-handoff stewardship is the lever for diagnosing what changed.
The honest comparison against the alternatives.
A commission is not the right answer for every operator. The mid-market operator with a workflow that matches a horizontal SaaS product's calibration target is better served by the product. The operator with a five-to-ten-year horizon and an AI investment runway of roughly $5 million or more (an estimate) is better served by an internal hire; one at an estimated $500 million-plus in revenue is better served by a Big Four engagement. We will tell the operator which of those alternatives fits if a commission does not.
The honest case for a commission is narrow on purpose. Established operators with a named workflow constraint, with stack systems that the product market does not represent well, with the budget runway for the fixed fee, with the cloud posture to run the system inside their own tenant. Operators in that narrow band, per the pricing page, are where the math works.
Why we publish the comparisons, the rankings, and the boundaries.
Most consulting houses do not publish ranked comparisons against their competitors, do not publish the boundary of what they will not build, and do not publish fixed-fee pricing bands. We publish all three because the operators we want to commission for are the operators who reward that transparency with a faster booking. The never-overbook rule means we are not optimizing for top-of-funnel volume. We are optimizing for the right four operators each quarter. Publishing the comparisons, the rankings, and the boundaries selects for those operators. See the full list of who we will and will not build for on the custom builds page.
FAQ.
Four questions come up on nearly every manufacturer audit call: how long a commission takes, what is expected of the operator, whether a build means replacing staff, and what happens if the diagnosed build does not work. The answers below cover all four in plain terms.
Does a commissioned build mean replacing staff?
No. The build automates the named workflow; the shop's own staff still own the judgment calls it does not make. This is a fixed-fee commission, not headcount reduction.
What happens if the diagnosed build does not work?
The production-build installment is not paid until after the prototype is validated against the operator's real shop-floor data, which typically ships in 7 to 10 days after the audit. If the prototype does not address the named constraint, the engagement stops before that installment, and the operator is not billed for a system that does not work.
See custom AI builds for what else gets commissioned.
Start with the $499 audit.
The AI-Ready Audit is $499. The report arrives the same day, as a private link and a PDF, with a 5-minute video walkthrough and a 20-minute call. If it has no value you get the $499 back, and every quarter your AI answers, rankings and money leak are re-checked free.
$499, money back if no value. No pitch. A written map you keep either way.
Next step
Start with the $499 audit. Bring the ERP platform, the quoting spreadsheet or process, and the production step where schedule accuracy breaks down. The call identifies whether a custom build, an off-the-shelf product, or an ERP configuration change fits the constraint. The call is part of the audit; no obligation after it.