For tax, accounting, consulting, and professional-services operators who know AI should help — and are tired of prompt tips, vendor demos, and ad-hoc ChatGPT no one will defend on a real client file.
Real work depends on private documents, templates, precedents, judgment, source-of-truth materials, review standards, output formatting, and confidence that the AI result is not quietly wrong.
Generic AI training teaches features. It does not turn one messy workflow into a reviewable work product. What you keep running into instead:
That is what we build in a day. One workflow. One artifact. One review gate you will actually defend in front of a client or the partner who signs.
A schematic for turning a repeated workflow into something a professional can sign their name to. AI drafts, searches, extracts, compares, summarizes, or assembles. A human reviews, decides, approves, and owns the final work.
A short diagnostic conversation. No obligation. No raw private client files needed — sanitized descriptions are fine. If there's no workflow worth pursuing, the recommendation is no-build.
For professional-services operators who know AI should help but do not know where to start. We pick one repeated workflow you bring, look at it together, and decide: Lab, 1:1 implementation, Private Workflow Factory sprint, nurture, or no-build.
Built from private professional-services workflow experiments — tax, proposal, outreach, ops. The useful pattern was the same every time: map the real artifact, sources, review gates, and implementation path before touching tools.
Director-level tax workflow inside a Big Four practice. Repeated proposal-style artifact, private source materials, local/private model setup, human review at every gate. Strongest current proof — still beta until measured on a live proposal end-to-end.
For a clinical genomics company: a repeated discovery and outreach sequence to identify patient-serving clinics and start a conversation with them. AI assists the finder and first-pass outreach; clinical operators own anything that actually leaves the office.
A repeatable outreach package for a B2B sales operator: mapped sequence, source list, and explicit human-decision points. Cut ad-hoc ChatGPT use, kept the rep in control of every message that goes out.
For coaches and creators running paid programs through Instagram DMs: mapped the repeated sales-conversation pattern, where AI drafts and triages, and where the operator stays in control of every reply before it sends.
Concept work with property agents: turn a steady stream of inbound leads into matched listings without losing the agent's judgment on which buyer actually fits which property.
An SME operator wanted to "fully automate" a purchase-order workflow. After the diagnostic, we narrowed scope honestly: AI assists extraction and matching; humans approve exceptions. No vendor was bought; no lock-in introduced.
An agency engagement where the honest diagnosis was no-build at that scope. We refunded rather than ship something that wouldn't hold up under review. The pattern stuck and now informs the diagnostic up-front.
The diagnostic itself runs on description, structure, and sanitized samples. No raw confidential client material is required to start, and nothing becomes a public case study without explicit permission.
If you do not leave the full-day Lab with one mapped workflow and a concrete next step — you get a free 1:1 follow-up or your money back.
And on the diagnostic side: if the conversation does not reveal a workflow worth pursuing, the recommendation is no-build. No forced sale.
Years sitting next to people doing the actual work — directors drafting tax memos, ops leads chasing purchase orders, founders writing proposals at midnight, agents matching leads to listings — and watching them try to bolt AI onto the side of it.
The pattern is almost always the same. The tool is fine. The prompt is fine. The workflow was never mapped. Nobody agreed on the artifact, the sources, or the review gate. So "AI adoption" became a synonym for "individuals paste things into ChatGPT and hope."
The Lab is the smallest unit of useful work designed around that. One day. One workflow. One reviewable artifact. If it's worth doing, you can feel it by lunch. If it isn't, we don't pretend.
Then the answer is no-build, and the Workflow Diagnostic will say so. We'd rather tell you not to do the Lab than take your money for one that produces a polished artifact nobody uses.
The Diagnostic exists for exactly this reason: it sorts "this is worth a Lab" from "1:1 implementation" from "Private Workflow Factory sprint" from "nurture" from "don't bother." All of those are legitimate outcomes.
No. The diagnostic works from your description of the workflow — the shape of the artifact, the sources it depends on, the people who touch it. Raw client files are never uploaded, transmitted, or required to begin. If we eventually look at samples (typically during the Lab itself), they're sanitized first, on your machines.
No. Prompts are downstream of the workflow. We design the workflow first — what the artifact is, what the sources are, where AI assists, where the human reviews. Prompts that survive contact with a real client artifact fall out of that design naturally. We do not sell prompt libraries.
Whichever ones fit the workflow and your existing licences. The Lab is tool-agnostic. We've worked with teams running everything from enterprise Microsoft 365 + Copilot to a single shared ChatGPT Team seat to fully local models on the firm's own hardware.
The AI-assistance plan you walk out with is portable: it documents what good looks like, not which vendor is meant to produce it.
A short, defensible human-review checklist your team can run before any AI-assisted artifact leaves the office. Typical items: source provenance, factual accuracy spot-check, judgment calls the human owns, sign-off owner, escalation path for exceptions. It looks like a real audit checklist, not a "is this output good?" thumbs-up.
Then we map the workflow anyway and design the review gate, and the Lab outcome includes a memo describing exactly what an AI-assisted version would look like and what data classes it would need to touch. That memo becomes the conversation you take to compliance. We've seen several "blocks" turn into "approved with conditions" once the workflow and review gate were drawn clearly.
Optionally, yes — the 1:1 paid implementation starts from US$1,500. There's also a Private Workflow Factory sprint for larger scopes, quoted once the workflow, source boundary, buyer, and review owner are clear. We will not sell implementation before the Diagnostic / Lab; we don't know enough to scope it honestly.
Yes, if you produce a repeated artifact where accuracy and judgment matter — proposals, client memos, position papers, research, recurring reports. The Lab is scoped per workflow, not per headcount.
It means: a real version of the artifact you already produce — with the AI-assisted steps, sources, and human review gates drawn explicitly underneath it. A partner or client could trace any line back to its source, judgment call, and reviewer. That's the bar.
The Workflow Diagnostic is free. Short. No raw client files. If there's no valuable workflow to map, the answer is no-build — and you've lost an hour, not a contract.
A calendar invite is on the way to . You'll get a short prep note 24 hours before — nothing more than a couple of sentences about your workflow. Bring no files; just be ready to talk through it.