AI implementation consulting
AI consulting that ends in something running.
Most small businesses do not need an AI strategy. They need someone to look at how the work actually gets done, point at the three places AI would pay for itself, and then help get those three things live. That is the whole engagement.
A good fit if
- An owner or ops lead who knows AI could help but not where to start
- A business already paying for tools like ChatGPT with nobody sure what they are getting
- You want recommendations from people who build this, not people who only advise
Probably not a fit if
- You need an enterprise transformation programme with a steering committee
- You want a report to show a board, with no plan to act on it
- The decision has already been made and you only need someone to agree
What you get
Deliverables, not activity.
Workflow teardown
Where hours and money actually go in your business, from interviews with the people doing the work.
Build, buy or skip list
Each opportunity with a recommendation: an off-the-shelf tool, a custom build, or not worth it yet. With the reasoning, not just the verdict.
Implementation plan
What to do first, what it depends on, what it will cost to run each month, and how you will know it worked.
Hands-on rollout
We set up the tools, build what needs building, and train your team on the result. Or hand the plan to your own developers.
How it runs
Four steps. No surprises.
- 01
Listen
Short interviews with the people doing the work and a look at the tools you already pay for.
- 02
Rank
Opportunities sorted by payback, risk and effort. Usually two or three stand out clearly.
- 03
Decide
A working session where you pick what happens first. No 80-page deck.
- 04
Implement
We build or configure the first item and measure it before touching the second.
Why most AI consulting does not stick
The usual engagement ends with a strategy document and a list of use cases. Then nothing happens, because the people who wrote it do not build, and the people who build were not in the room.
We build AI products for a living, including our own. That changes the advice. We know what an agent costs to run per month, which integrations break, and which ideas sound good in a workshop but fall apart on real data.
Where AI usually pays back first in a small business
The first wins are almost never the exciting ones. They are the tasks everyone quietly hates.
- Inbox triage: sorting, tagging and drafting replies to routine email
- Document handling: pulling data out of invoices, forms and contracts
- Lead follow-up: making sure every enquiry gets a fast, relevant first reply
- Internal search: answering staff questions from your own docs and policies
- Reporting: turning raw exports into the summary someone builds by hand every Monday
When the right answer is to buy, not build
If a mature product already does the job, buy it. Custom builds make sense when your workflow is genuinely different, when the data cannot leave your systems, or when the off-the-shelf tool would cost more per seat than a build costs to run.
Aumiqx also publishes AI tool reviews, some of them sponsored. If we recommend a tool whose maker we have a commercial relationship with, we say so in the recommendation itself.
Proof · things we run ourselves
We build on the patterns we use in our own products.
SalesClawd
Our flagship product, liveAn AI marketing employee for small businesses. Three autonomous agents run SEO, email and bookings, with a human approval queue in front of every action.
The SEO agent coordinates ten specialist Claude agents in parallel, each with its own tools and evidence trail. Every change is read back from the live source and verified before anyone sees it. Fastify, Next.js, Postgres with Drizzle, BullMQ on Redis, the Anthropic SDK.
See SalesClawdMeet Buddy
Internal toolA meeting co-pilot we use on our own client calls: context before the call, live notes during it, follow-ups after.
A Manifest V3 Chrome extension streams meeting context to an MCP server, which hands work to a swarm of Claude agents. GitHub device-flow auth, no stored passwords.
Tools we work with
Questions
Asked before buying.
What does an AI implementation consultant do?+
They find where AI will save your business time or money, recommend whether to buy a tool or build something custom, and then help put it into production. The difference from a strategy consultant is that the engagement ends with something running.
Is AI consulting worth it for a small business?+
It is worth it when it is short and ends in implementation. A small business rarely needs a long strategy phase; it needs two or three well-chosen changes that pay back within months.
Do we need our own developers?+
No. We can build and hand over everything. If you do have developers, we can hand them the plan and the architecture and support them instead.
Do you have commercial relationships with AI tool vendors?+
Some. Aumiqx publishes AI tool reviews, a few of them sponsored. Any recommendation involving a vendor we work with is disclosed in writing, and we will tell you when an off-the-shelf tool beats anything we could build.
Often paired with
Tell us what is eating your week.
A 30-minute call with the person who would build it. You leave with an honest read on whether it is worth doing, even if the answer is no.