Five industries. Hard-won pattern recognition.

Every build begins with the $499 AI-Ready Audit. The call comes with the audit. Both sides leave with the constraint written down in a single sentence. Either party can stop there with nothing further owed. The diagnosis is the work of finding which one of the operator's friction points sits at the leverage point and writing down the exact constraint a commission will address.

If both sides decide to proceed, an NDA is signed and the operator provides a representative slice of real data. Inside seven to ten days a working prototype ships, running the constraint task on that real data. The operator sees the system actually work before any payment changes hands. If the prototype does not perform to the target written down after the audit, the operator owes nothing and keeps the work product.

If the prototype performs, the fixed-fee production commission begins. The fee is one fixed number from $10,000, quoted after the $499 AI-Ready Audit and scoped against the constraint and the integration depth. Build runs four to seven weeks. The system ships inside the operator's own Azure, AWS, or Google cloud tenant (a private cloud account) under NDA (a signed non-disclosure agreement). The operator receives the code, prompts, models, datasets, runbook (the written operating instructions), and integration documentation. The operator owns the system at handoff. There is no proprietary runtime to license and no per-seat fee to renew.

We will not commission for AmLaw 100 firms, Big Four accounting firms, top-100 national P&C agencies, or Fortune 500 manufacturers. Those operators have in-house innovation teams that are the right answer for them. We will not commission a per-seat SaaS (software you rent by subscription) subscription product; ColabContent is a custom build house. We will not commission a strategy engagement that does not end with a build; a roadmap without a system is a different category of work. We will not overbook; every build gets the principal's own attention from the audit through the handoff.

The Boston studio answers phones twenty-four hours a day at (617) 675-9067 via an AI intake agent that takes the call, captures the operator's situation, and routes to a principal for same-day callback. The email line is support@colabcontent.com. The booking page is at colabcontent.com/contact. The reach lines are real. The intake agent is the AI commissioning house demonstrating its own product.

The process page walks through the four phases of a commission. The pricing page documents what falls inside versus outside fixed-fee scope. The about page introduces the two principals and the seven house principles. The FAQ answers the questions buyers ask before commissioning. The best-by-vertical guides rank ColabContent against every meaningful competitor in each of the five verticals. The case studies are field reports from prior commissions.

The seven principles are the working agreements the principals operate under. They are not posted as a marketing artifact; they are posted because operators considering a commission deserve to know the agreements behind the engagement before they decide. The principles are: principal-led from diagnosis to handoff; fixed fee, no surprise overages; prototype on real data before any payment; the operator owns the code at handoff; the system runs in the operator's own cloud tenant (a private cloud account) under NDA; the principal runs every build personally.

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 post-handoff stewardship ($997 a month, cancel on 30 days notice) is the lever for diagnosing what changed.

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, a $5M AI investment runway, and the willingness to spend twelve months building infrastructure before shipping the first production workflow is better served by an internal hire. The operator at $500M-plus revenue with stakeholder counts that justify a Big Four engagement is better served by that motion. 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 are where the math works.

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 pricing page for how the fixed-fee bands are structured.