Data
Where it lives, who can reach it, what condition it's in, and whether it's complete enough to support the use cases you're considering. Most AI projects fail here, and they fail quietly, six months in.

AI Services · Readiness Audit
Two weeks. A flat fee. An honest answer about whether your organization can actually support AI right now.
Definition
A structured assessment of whether your organization has the data, systems, workflows, staffing, and governance in place to adopt AI successfully — delivered as a scored diagnostic that names what's ready, what's blocking you, and what has to be fixed first.
It answers whether you can, not what you should build.
Free self-assessment
You don't need to hire anyone to get a rough read. Answer honestly — yes or no, no maybes. Ten questions across the five areas that determine whether an AI initiative survives contact with reality.
You can name where your most important operational data actually lives, and reach it without filing a ticket.
8–10
Your foundation is solid and your constraint is direction, not capability. Skip the diagnostic and go straight to deciding what to build.
5–7
This is where most organizations land, and it's exactly what the audit is built for. You have gaps you can't see clearly enough to sequence. Two weeks gets you the map.
0–4
A low score isn't a verdict, it's a warning that a large AI investment right now would likely fail for reasons unrelated to the AI. The audit is the cheapest way to find out which foundations to fix first.
Scored lower than you expected? That's the useful outcome. Every question maps to something we assess in depth — and to something fixable.
Assessment dimensions
The checklist is the surface. Here's what a real assessment looks at underneath it.

Before you commit a year and a budget line to an AI initiative, it's worth knowing whether the foundation holds. We assess your data, systems, workflows, team, and governance — then tell you plainly what's ready, what isn't, and what it would take to close the gap.
Sometimes the answer is go. Sometimes it's not yet, and here's the specific reason. Both are worth knowing before the money moves.
Where it lives, who can reach it, what condition it's in, and whether it's complete enough to support the use cases you're considering. Most AI projects fail here, and they fail quietly, six months in.
What your existing stack can and can't connect to. Integration debt is the most commonly underestimated cost in an AI implementation, and it's usually invisible until a vendor contract is already signed.
Where time actually goes, measured rather than assumed. We look for the expensive repetitive work, not the visible annoying work. They're rarely the same thing.
Who would own this, who would maintain it, and whether your team has bandwidth to absorb a change this year. A tool nobody has time to adopt is a subscription, not a solution.
Your regulatory exposure, your data-handling obligations, and what review process would need to exist before AI output reaches a student, donor, patient, or the public.
Investment
$4,500
Flat · two weeks · credited forward
You know the cost before you start, and it doesn't move. Two weeks from kickoff to findings session, priced flat so the incentive is an honest answer — not a longer engagement.
Credited forward. If you start any engagement with us within ninety days of the findings session — consulting, a strategy sprint, a prototype build — the full audit fee comes off that project. If you don't, you still have the report, and you owe us nothing further.
We price it this way on purpose. An assessment that only pays off if you hire us for the next thing isn't an assessment, it's a sales call with a deliverable attached.
Deliverables
Everything below is handed over whether or not you work with us again.
Process
The timeline is fixed rather than estimated. Here's what happens inside it.
We agree on which workflows are in scope, who we need to talk to, and what data access boundaries apply. You leave with a schedule and a short list of things to gather.
Four to six conversations with the people doing the work, plus a review of your tooling and data structure. We talk to operators, not only leadership — the gap between how work is described and how it happens is usually where the findings are.
Each of the five dimensions gets scored against a consistent rubric, so your result is comparable to a benchmark rather than a matter of our opinion. Blockers get separated into “fix before you start” and “fix as you go.”
A working session walking your team through what we found, followed by the written report. We stay for the questions, including the uncomfortable ones. The report is written to be forwarded to someone who wasn't in the room.
Qualification
What comes next
The audit tells you whether you can and where the gaps are. Where you go next depends on what it finds.
Four to eight weeks producing a prioritized, sequenced roadmap. The natural next step when the audit says you're ready and the question becomes what to build first.
Go nextOne week, one room, a ranked roadmap. For teams who came out of the audit with candidate ideas and momentum they don't want to lose.
Go nextA working version of the thing, built small enough to test cheaply. For when the audit confirms one opportunity is clearly worth proving out.
Go nextCredibility
Public universities and private colleges, foundations and nonprofits, health systems, and civic institutions — places where a decision has to clear a privacy review, a procurement process, and a board before it ever reaches a user. Those constraints are exactly why an honest readiness answer is worth more there than anywhere else. A failed pilot at a startup is a bad quarter. At a university it's a governance problem.
Questions
Two weeks, a flat fee, and a report you can forward. Tell us where you are and we'll tell you honestly whether the audit is the right next move.
Not sure yet? Take the 10-question read.
Book the audit