Privacy Policy.
ColabContent's privacy posture: operator data stays inside the operator's own cloud tenant (a private cloud account) under NDA (a signed non-disclosure agreement). Diagnosis-call notes are confidential. Prototype runs on operator data inside a sandbox that the operator controls. Production builds run inside the operator's Azure, AWS, or Google tenant. No data resale, no cross-client model training.
Deliberately short, because we deliberately collect very little.
Last updated · April 2026.
ColabContent LLC ("we") operates colabcontent.com. This privacy policy explains what we collect, why, and what your rights are. It is deliberately short because we deliberately collect very little.
What we collect
If you fill out the contact form or enroll in the AI-Ready Course, we collect: your name, email, company, revenue range (form only), and the message you send us. That's it.
We do not use advertising or tracking pixels. We do not use Google Analytics. We use a simple server log (IP, page, referrer) that we retain for 30 days for performance and abuse monitoring, then discard.
Why we collect it
This section states directly why any information collected through the site is gathered at all: solely to respond to the person who submitted it, never to build a marketing list or a data product. The single sentence below covers the full policy; there is no secondary use of contact information anywhere in this practice.
Exclusively to respond to you. We do not sell, rent, trade, or share your data with third parties.
This section separates the two kinds of email a submission can generate: transactional messages such as diagnosis confirmations and course lessons, sent through the site's email provider, and marketing email, which this practice does not send at all. The distinction sets the limit on what any address on file will ever receive.
Transactional email (diagnosis confirmations, course lessons) is sent from our email provider. Marketing email is not something we do.
Your rights
This section spells out what control a person has over their own data on file: the right to request a copy of it, a correction to it, or its outright deletion, submitted by email, with a response guaranteed within seven days of that request being received.
You can request a copy, correction, or deletion of your data at any time by emailing privacy@colabcontent.com. We'll respond within 7 days.
Cookies
This section is short because the practice is short: exactly one first party cookie is used across the entire site, and its only job is remembering that a visitor already dismissed the seats banner. No analytics cookie, no advertising cookie, and no third party tracking script sits behind it.
We use exactly one cookie: a first-party session cookie to remember you've dismissed the seats banner. No tracking. No third parties.
Contact
This section gives the single channel for any privacy question not already answered above: a direct email address that reaches the people who wrote this policy, read every message that arrives, and are the ones who would action a rights request under the section above.
privacy@colabcontent.com. We read every email.
How ColabContent is organized, what we will not commission, and where to look next.
ColabContent is a custom AI consulting firm in Boston that builds systems its clients own. The entries below explain how the firm is organized, what it refuses to build, and where to read next, so an owner can judge the fit before ordering the $499 AI-Ready Audit.
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 (a signed non-disclosure agreement) 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.
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. That stewardship, when the operator chooses it, costs $997 a month and cancels on 30 days notice.
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, 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.
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.
No pitch. Money back if the audit has no value. A written map of the two line items bleeding your business.
Document maintenance
This document is reviewed quarterly and updated when material changes are required. Material changes are announced via the contact email and via banner notice on the homepage. The current version supersedes any prior version. If you require a copy of a prior version for archival or audit purposes, contact us through the contact page and we will provide it within 5 business days.
Questions about this document should be directed through the contact page. We respond to legal inquiries within 5 business days under normal circumstances and faster for urgent matters. For data subject requests under GDPR, CCPA, or similar regimes, the response window is 30 days from the date of the request as required by applicable law.
This document applies to colabcontent.com, its subdomains, and any communication from the ColabContent editorial team or commercial team. It does not extend to third-party websites linked from colabcontent.com or to platforms used in the course of commission engagements unless explicitly noted.
Frequently Asked Questions
These answers go past the policy text above into the specific questions people actually ask before sending real business data: whether any of it trains a model, who can see it during a build, how to request deletion, and whether the site tracks visitors with cookies.
Does ColabContent use my data to train any AI model?
No. Diagnosis-call notes, prototype data, and production data never leave the operator's own cloud tenant or feed a cross-client model; there is no data resale and no shared training set.
Who can see the data during the prototype and build phases?
Only the principal running the engagement, under the signed NDA, working inside a sandbox or cloud tenant the operator controls.
How do I request my data be deleted?
Email privacy@colabcontent.com; requests for a copy, correction, or deletion are answered within 7 days, and data-subject requests under GDPR or CCPA are answered within the 30-day window the law requires.
Does the site use tracking cookies?
Exactly one first-party cookie, used only to remember that a visitor dismissed the seats banner. No analytics cookie and no advertising cookie run on this site.