How much does the AI readiness audit cost?

It's a fixed price, scoped on a free call. We don't publish a rate card because the price depends on how many systems, teams, and workflows are in scope — after the discovery call you get a written proposal with a single fixed fee, the exact deliverables, and the dates, so there are no open-ended hourly surprises.

Do we have to hire you for the build afterward?

No. The roadmap and estimate are yours to use however you choose — with us, with your internal team, or with another vendor. We write them so any competent engineering team can act on them.

How much of our team's time does the audit take?

Mostly interviews of about an hour with the people closest to each workflow, plus a named point of contact to arrange system access. We agree the list in advance so nobody is surprised.

What if the audit finds AI isn't a good fit right now?

Then the roadmap says so and explains why — for example, data that needs cleanup first or a process that an off-the-shelf tool already handles well. A clear 'not yet' is a useful result.

AI readiness audit

An AI readiness audit that ends with a roadmap you can act on

The AI readiness audit is a two-to-four-week paid engagement for businesses that know AI should help but aren't sure where to start, what it will take, or what it will cost. We study how work actually gets done, what data and systems you have, and where the risks are — then hand you a written AI-use roadmap and a build estimate for the opportunities worth pursuing.

Start your project

Who the audit is for

The audit is built for owners, operators, and technology leaders who are being asked about AI and want a grounded answer. It fits well when you have several possible use cases and no clear way to rank them, when a vendor has pitched an AI product and you want an independent view, when leadership wants a budget number before approving a build, or when teams are already using AI tools informally and you need to understand the exposure.

It is not a sales exercise for a build. Some audits conclude that the best next step is an off-the-shelf tool, a process change, or waiting until your data is in better shape. The roadmap says so plainly, and you're free to take it to any team — ours or someone else's.

What's included

Every audit covers the same core areas, weighted toward what matters most for your business. We agree the scope, the people we'll interview, and the systems we'll review in writing before the audit starts.

Stakeholder interviews with the people who do the work, not just leadership
Workflow mapping for the processes with the most manual effort
Data review: what you have, where it lives, its quality, and who can access it
Systems and integration review of your CRM, ERP, help desk, and internal tools
Risk review covering privacy, security, compliance, and vendor lock-in
Review of AI tools already in use across the business
Build-versus-buy analysis for each opportunity
Prioritized roadmap with effort, dependencies, and a build estimate

Timeline

Most audits run two to four weeks, depending on how many teams and systems are in scope. A typical shape looks like this:

Week 1 — Kickoff and interviews

We confirm goals and success criteria, get read access to the documents and systems in scope, and interview the people closest to the work to find where time and money actually go.

Weeks 2–3 — Analysis

We map the highest-effort workflows, test data quality against each candidate use case, check integration paths, and assess risk. Where it helps, we run quick feasibility checks — for example, testing whether a model can reliably extract fields from a sample of your real documents.

Final week — Roadmap and readout

We write the roadmap and walk your team through it in a live readout, answering questions and adjusting priorities before the final version is delivered.

Deliverables

You receive a written AI-use roadmap and a build estimate. The roadmap ranks each opportunity by expected value, effort, risk, and data readiness, and explains the reasoning so your team can challenge it. For the top opportunities, it describes the proposed approach, the systems it touches, what a first version would include, and how success would be measured.

The build estimate breaks the recommended work into phases with a scope and a price range for each, so you can budget for the first step without committing to the whole program. You also get the interview notes, the workflow maps, and the data and risk findings — the raw material behind the recommendations, not just the conclusions.

What happens after the audit

A common next step is to take the top-ranked opportunity into a fixed-price AI discovery sprint and prove it on real data before committing to a full build. You can also go straight to production with our AI development services, hand the roadmap to your internal team, or use it to evaluate vendors. If the review surfaces concerns with AI systems you already run, our AI security audit goes deeper on those. Every engagement starts with a free discovery call, where we learn your goals, systems, and constraints before proposing a scope.

Frequently asked questions

A short, paid engagement — usually two to four weeks — where we review your workflows, data, systems, and risks, then deliver a written AI-use roadmap and a build estimate showing which AI opportunities are worth pursuing and in what order.