AI consulting that ends in working systems
An AI consultant for owners doing $1M to $20M who want straight answers: which tools are worth licensing, which processes are worth a custom build, what staff can safely paste into a chatbot, and what it all takes to run. Then the same team builds the first project.
- A written AI use policy your staff can follow
- Vendor data terms read before you sign
- Every recommendation tied to a process and an owner
What owners bring to a first call
Staff already use AI, unofficially
People paste client emails and spreadsheets into personal ChatGPT or Gemini accounts. Nobody knows what left the building or under which terms.
Every vendor now sells an AI add-on
Your CRM, help desk and accounting software all pitch AI features, and each demo looks good. None has been tried on your actual documents.
Licenses bought, nothing changed
Microsoft 365 Copilot or ChatGPT seats were rolled out, usage dropped after a month, and no process was redesigned around them.
What a consulting engagement covers
Short, fixed-scope work that ends in decisions you can act on.
Process and time review
Interviews with the people doing the work, plus a look at the inboxes, queues and spreadsheets behind it. Each idea is scored on hours, error cost, data sensitivity and how messy its inputs are.
AI use policy
Plain rules for which tools are approved, what data may go into them (client PII, financial records, contracts), and when a person must review AI output before it is sent.
Vendor data terms review
We read the terms for tools you are weighing: whether business data trains models, how long prompts are kept, whether zero-retention or regional hosting is offered, and what admin controls exist.
Buy, build or skip calls
For each use case: a feature already inside HubSpot, Zendesk or Microsoft 365, a licensed tool, or a custom build. Most firms need fewer custom builds than they expect.
Staff training on real tasks
Sessions built on your own documents covering drafting, summarizing and checking output, plus where models still fail, such as invented citations and arithmetic.
Build of the first project
When a custom build wins, we scope it in writing and build it, so the advice gets tested on live work instead of sitting in a folder.
Who hires an AI consultant like us
Owners starting from zero
A first look at where AI fits, before any commitment.
Law firms
Tool and policy choices weighed against confidentiality and supervision duties.
Accounting and tax practices
Tool choices checked against the written security program the FTC Safeguards Rule expects.
Insurance agencies
Decisions on which client and policy data can go into which tools.
Teams with a stalled pilot
A review of why it stalled and what to change.
Companies weighing agents
Which agent roles make sense at your size.
Why our advice holds up
We build what we recommend
Because we take on the build, we cannot recommend something that only works in a demo. That keeps advice tied to what the APIs and your data allow.
No resale margins
We do not resell software licenses or take referral fees, so telling you to use a feature you already pay for costs us nothing.
Skeptical of AI marketing claims
The FTC has taken action against companies that overstated what their AI could do. We test vendor claims on your files before you rely on them.
A policy staff will actually read
A one-page AI use policy people follow beats a long one nobody opens. Your counsel reviews it before it goes out.
“He got me 9 sales in my first 7 days of launching our campaign, which exceeded my expectations!”
Common questions
What does an AI consultant do?
Works out where AI will save time or cut errors in your business, which tools to use and which risks to manage. Our version ends with a written plan and, if you want it, the first build.
Do small businesses need an AI consultant?
Not always. If the need is a few licenses and a usage policy, a short engagement covers it. Consulting pays off when several vendors need comparing, sensitive client data is involved, or a process needs custom work.
Is it safe for staff to use ChatGPT, Claude or Copilot with client data?
Consumer accounts and business plans carry different terms. Business and API plans from the major providers generally exclude your data from model training by default, and some offer shorter or zero retention to eligible customers. We check the current terms for your tools and write the policy around them.
Should we buy Microsoft 365 Copilot or build something custom?
Copilot is strong inside Outlook, Word, Teams and SharePoint for drafting and search. It does not run a multi-step process across QuickBooks, your CRM and industry software. Many clients end up with both: licenses for general work and a custom build for one process.
Will you recommend tools you sell?
We do not sell software licenses. If a tool you already pay for covers the need, that is what we recommend.
What do we get at the end of the engagement?
A ranked list of use cases with estimated hours saved, a buy, build or skip call on each, a draft AI use policy, notes on vendor data terms and a scoped first project you can give to us or anyone else.
Start with a quick AI assessment
The 2-minute AI audit gives you a readiness score and the questions we would ask on a first consulting call.
- Interview the people doing the work
Short sessions with the staff who handle the inbox, the books and the CRM, because owners rarely know where the minutes go.
- Try top ideas on your own files
The leading candidates are tested on a sample of your emails or documents, so the advice reflects measured accuracy, not a vendor demo.
- Deliver a ranked plan and a policy
A short written plan: what to license, what to build, what to skip and in what order, plus a draft AI use policy for your counsel to review.
- Build the first item, or step back
You can have us build the top project, give it to your own team, or stop there. The plan carries no lock-in.