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Five systems we commission most often.

Solutions for mid-market operators delivered as a custom commissioned build. ColabContent commissions custom solutions at fixed fee (from $10,000), integrated with the operator's actual stack, with code owned at handoff. The system runs inside the operator's own cloud tenant (a private cloud account) under NDA, with a working prototype within 7 to 10 days before payment.

Key Takeaways

  • Solutions for mid-market operators delivered as a custom commissioned build.
  • ColabContent commissions custom solutions at fixed fee (from $10,000), integrated with the operator's actual stack, with code owned at handoff.
  • Every system we build is bespoke.
  • Click any solution below to see the typical pain, the approach we take, and the numbers we see in practice.
  • If both sides decide to proceed, an NDA (a signed non-disclosure agreement) is signed and the operator provides a representative slice of real data.
The five custom AI systems ColabContent commissions most often for mid-market operators: workflow automation, knowledge retrieval RAG (retrieval-augmented generation), revenue operations AI, content operations AI, and bespoke systems, under one fixed-fee engagement model
Five recurring shapes, one engagement model.

After forty engagements, five categories account for nearly all of the work. Every build is bespoke, but the patterns are known, and the benchmarks are real.

CategoriesFive
Custom scopeEvery time
Timeline4-14 weeks
GuaranteePrototype before payment

Every system we build is bespoke. But after forty engagements, five shapes account for nearly all of the work we commission. Each is a category, not a product, we shape the specifics to your operation, your stack, and your team.

Click any solution below to see the typical pain, the approach we take, and the numbers we see in practice.

Methodology

How ColabContent thinks about this layer of the work.

Every layer of a business gets the same treatment: find the constraint, price it, and build only what removes it. The notes below set out how ColabContent approaches this particular layer, which patterns recur across the businesses we have worked with, and where a custom system pays off first.

How ColabContent is organized.

ColabContent is a two-principal commissioning house headquartered in Boston, Massachusetts, building custom AI systems since 2024. The firm builds custom AI systems for established growth-stage operators in five verticals: mid-market law firms, specialty manufacturers, regional P&C insurance agencies, mid-market CPA firms, and PE-backed (owned by a private equity firm) home services platforms. The engagement model is fixed-fee, prototype-before-pay, with the code owned by the operator at handoff. The firm never overbooks; the principal runs every build personally.

The engagement model in three paragraphs.

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. 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.

What we will not commission.

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 reach lines.

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.

Where the rest of the documentation lives.

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.

A note on the seven house principles.

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 under NDA; the principal runs every build personally.

Buyer worksheet

How this solution category fits into the engagement model.

A solution category is only useful once it is attached to a specific constraint in a specific business. The entries below show where this category sits in the sequence, from the $499 AI-Ready Audit through a working prototype to a fixed-fee build the business owns, and when it is the wrong first system.

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 (software rented by subscription rather than owned) 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.

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.

Ready when you are

Start with the $499 audit.

The AI-Ready Audit is $499. The report arrives within 3 business days 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.

No pitch. Money back if the audit has no value. A written map of the two line items bleeding your business.

Related reading: Custom AI Consulting FAQ for Mid-Market Operators.

Related reading: How a Custom AI Commission Runs, Step-by-Step.

All Solutions

Frequently Asked Questions

These answers help a reader choose between this Solutions grouping and the vertical industry pages elsewhere on the site, and clarify how pricing works across the different solution types listed below, since that is the question this grouping raises most often.

How is this Solutions page different from the vertical industry pages?

Industry pages (law, CPA, insurance, manufacturing, home services) describe workflows by vertical; Solutions groups the same commissions by system type (bespoke AI, knowledge and RAG, revenue operations) for an operator who already knows which kind of system they need.

Do all solution types cost the same?

No. Every commission is fixed-fee from $10,000, but the number depends on integration depth and the systems being connected, quoted after the $499 AI-Ready Audit names the workflow.

Can a solution span more than one of these categories?

Yes; a revenue-operations build often needs a knowledge or RAG component underneath it, and the audit scopes that as one commission rather than two separate engagements.