AI consulting for small and mid-size businesses, starting with one job worth handing to AI
We help small and mid-size companies decide where AI pays off. Then we set it up inside the systems you already run. A person on your team signs off on anything that reaches a customer.
Free, 30 minutes, and you'll leave with at least one clear next step.
Where do AI projects go wrong at companies like yours?
Most AI advice is written for big software companies with data teams. A 60-person business hits different problems.
The tool comes before the job
Someone sees a demo, buys a seat for everyone and hopes people find a use. Six months later, three people use it to rewrite emails.
The data underneath is a mess
Duplicate accounts, deals with no owner and order history stuck in another system. An AI reading that CRM gives wrong answers with full confidence.
The review has no owner
The AI drafts a reply, but no one is named to check it. So either nothing goes out, or everything goes out unchecked.
Company data ends up in personal accounts
Reps paste customer lists and pricing into free AI tools because no one gave them a safe option.
What does an AI consultant do for a company your size?
We start from the work, then pick the tool. We sit with your sales, service and operations people and list the jobs that eat hours. Think of reading new inquiries, answering status emails, chasing quiet accounts or typing call notes into HubSpot. Each job then gets matched to the simplest AI that can do it.
Often that's a tool you already pay for. HubSpot Professional and Enterprise plans come with a monthly allowance of AI credits, and many companies never touch it. Sometimes the job needs a custom AI workflow that reads your documents and checks your other systems. And sometimes a plain HubSpot workflow or a cleaner process beats any AI. We'll say so.
Which AI should you start with?
Find the line that sounds most like your business. That's usually the right first project.
"New inquiries sit in an inbox for days"
Start by having AI read each request and hand a rep a ready-made deal with the details filled in. Teams that get a lot of form fills or emailed requests often start here.
Custom AI workflows"We answer the same customer questions all day"
If your help articles are solid, HubSpot's Customer Agent can answer common questions in chat. Teams buried in the same five questions every day often start here.
Customer Agent"Our CRM is a mess"
Clean it up first. HubSpot's Data Agent can fill in missing company details, and every AI project after that gets better.
Data Agent"Our reps can't keep up with all our accounts"
An AI sales agent can watch accounts and draft notes for reps to approve. Companies with lots of past customers and a small sales team get the most from it.
AI sales agent"People already use ChatGPT or Claude for work"
Move them to a company plan, set rules for what data goes in and connect it to HubSpot with the right permissions.
Claude for business"Buyers ask AI tools who to buy from, and we're not named"
That's a website and reputation job. We start by checking what ChatGPT, Claude and Google's AI answers say about you today.
Generative engine optimizationHow do we decide what goes first?
We score each job on four things. How often it happens, how long it takes a person, what a mistake costs and whether the AI can reach the data it needs. A job that happens 40 times a day, takes 10 minutes and is cheap to get wrong beats a flashy job that happens twice a month.
For a service business, that might put sorting new leads ahead of an AI proposal writer. For a company with repeat buyers, reorder reminders based on order history might beat a website chatbot. Once we agree on the first job, we prove it with a fixed-scope AI pilot before we build anything else.
Rules every AI project follows with us
We write these down before anything goes live, and your team signs off.
- A named reviewer. One person on your team owns the AI's output and checks it on a set schedule.
- Drafts first. The AI starts by drafting, sorting and filling in fields. A person approves its work until it has a track record on your own records.
- Hands off the risky stuff. It never sends prices or quotes, promises ship dates, answers complaints, deletes records or changes account owners on its own.
- Unclear cases go to a person. When the AI isn't sure, it puts the item on a review list instead of guessing.
- Everything is logged. You can see what the AI did, when and why.
Which of your data can go into AI?
Early on, we sort your data into three groups with you. Most of it, like contact details, deal notes and help articles, is fine for a business AI plan. We read the provider's terms with you first. Some of it, like customer pricing and margins, only goes in for a specific job, and only the fields that job needs.
A small part may be off limits for cloud AI altogether. Think of cost sheets, legal files or anything under a contract that bans third-party AI. For those, we either leave them out or use private AI. The sort takes an afternoon, and it gives your team clear rules instead of guesswork.
If your staff are already pasting customer lists into free AI tools, we deal with that in week one. It's often the biggest risk we find.
AI starts with connected systems. Here's that work in practice.
When don't you need an AI consultant?
If you have an ops or IT lead who already knows which job to automate, HubSpot's help pages may be enough to switch on a built-in agent. If your team is under ten people and they mostly want help writing, a company Claude or ChatGPT plan and an hour of training will do it.
We'll tell you on the call if either fits. That's a fine outcome.
Examples by industry
The first AI job looks different in every business. These pages show what it tends to be in a few we know well.
- Manufacturing: sorting incoming requests and keeping reps on top of big account lists.
- Construction: keeping bids, jobs and follow-ups moving without retyping.
- Ecommerce: answering order questions and spotting repeat buyers who've gone quiet.
AI consulting questions
How is an AI consultant different from an AI software vendor?
A vendor sells one product and fits your problem to it. We start from the job and then pick the tool. That might be HubSpot's built-in AI, Claude or ChatGPT, a custom workflow or no AI at all.
Do we need developers or a data team on staff?
No. Most of our clients have neither. We need one person who knows the work, one who can approve the AI's output and access to your systems. We handle the technical side.
Which AI tools do you work with?
HubSpot's Breeze agents, Claude from Anthropic, ChatGPT and OpenAI's models, and HubSpot's MCP server, which connects AI tools to your CRM. We test them on your documents and pick what works best.
How soon should we expect results from AI?
A focused first project usually shows whether it works within a couple of months. Cleanup work comes first if the data isn't ready, and that adds time. We agree on a measure up front so you can judge it yourself.
Can you help if we don't use HubSpot?
For advice, AI search work and team AI rollouts, yes. For building agents into a CRM, we work in HubSpot. If you're on another CRM and thinking of moving, we do that too.
Is AI worth it for a company with 30 employees?
Often, yes, if one job repeats a lot. A small team that retypes 50 inquiries a week has a clear first project. If no single job repeats more than a few times a week, a company AI plan and some training may be all you need for now.
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Tell us the job you'd hand to AI tomorrow
Bring one task your team does by hand every day. We'll tell you which AI fits it, what it needs and whether it's worth doing now.