AI CONSULTING & STRATEGY — RANKED, COSTED, WITH A NO-LIST
Anyone can list what AI could do. The useful question is what’s worth doing.
We go through your actual processes, score them against four things that predict whether automation pays, and hand you a ranked shortlist with an estimated cost against each one — plus the list of ideas we think you should drop. No platform recommendations until we know what the work is.
✓ Ranked by return, not by novelty✓ A cost estimate against each item✓ An explicit “don’t build this” list✓ Vendor-neutral — including of us
If the honest answer is that nothing here is worth automating yet, that’s what the report says. It has happened, and those clients came back later.
In short: AI consulting here means looking at how your business actually runs, finding the handful of processes where automation would pay for itself within a year, and putting a number and a sequence against them. The deliverable is a document you can act on or take to another supplier — not a deck of possibilities and not a licence agreement.
Why most AI strategy work goes nowhere
A familiar pattern: someone runs a workshop, the whiteboard fills with forty ideas, everyone leaves energised, and eleven months later two pilots are half-finished and nobody can say what either one saved.
It fails for a boring reason. The ideas were generated by asking what AI can do, which produces an unranked list where a $200,000 vision sits next to a two-week win and nothing distinguishes them. Then the organisation picks the exciting one instead of the profitable one, because there was no reason on the page to do otherwise.
The fix is not more ideas. It is a scoring method applied to fewer of them, and the discipline to write down the ones you are choosing not to do so they stop being re-proposed every quarter.
The four things we score every idea against
None of these are about the technology. All four are things you can answer from inside your own business, and together they predict whether a project will be worth it far better than how impressive the demo looks.
01 — VOLUME
How often does it actually happen?
Four hundred times a month is a project. Six times a month is a person’s afternoon, and automating it will cost more than it saves for years. This one question eliminates roughly half of most idea lists, and it’s the one nobody asks in the workshop.
02 — TIME PER INSTANCE
How long does one take, honestly?
Including the interruption cost. A task that takes ninety seconds but breaks someone’s concentration four times an hour is worth more than the ninety seconds suggests. We ask the people doing it, not the people describing it.
03 — COST OF BEING WRONG
What happens on a bad output?
A mistyped internal tag is a shrug. A wrong number on a customer invoice is a phone call, a refund and a review. High error cost doesn’t disqualify a project, but it triples the engineering around it — approval gates, audit trails, rollback — and that belongs in the estimate up front.
04 — DATA READINESS
Does the information exist anywhere?
If the rules live in one person’s head and the records live in a spreadsheet somebody emails around, the first half of the project is archaeology. That’s often worth doing — but it should be priced as its own phase rather than discovered in month three.
What the scoring produces. Three groups rather than a ranked forty. Do now — high volume, real time saved, low error cost, data already available. Do after something else — worth it, but blocked on a system, a data problem or a process that needs fixing first. Don’t — with the reason written down, so it stops coming back.
Four ways to work with us on this
Most engagements start with the first and stop there until something is proven. That’s the intended shape.
These come up in most audits. We’d rather you read them here than pay us to say them.
A company-wide chatbot over “all our documents”
It is the most requested project and among the least successful. Documents contradict each other, half are out of date, and nobody owns the answer when it’s wrong. Narrow it to one department’s genuinely maintained material and it starts working.
Training a custom model when a prompt would do
Fine-tuning is occasionally the right answer and usually an expensive way to reach the same place. We only recommend it when we can name the specific thing a general model cannot do for you.
Automating the process the loudest person complains about
Annoyance and cost are different measurements. The genuinely expensive processes are usually the ones everyone has stopped noticing because they have always been that way.
Starting with the thing that would impress the board
The first project should be the one most likely to work, because its job is to buy credibility for the second. Ambition is better spent in quarter three.
What you get, and what it costs
The audit is a fixed fee, quoted before we start, scaled to how many processes and systems are in scope. It is deliberately affordable relative to a build, because its whole purpose is to stop you spending a build-sized budget on the wrong thing.
You get a written report rather than a presentation: the processes we looked at, what each one currently costs in time, the score against all four criteria, an estimated build cost and running cost for the ones worth doing, the sequence we’d suggest, and the explicit no-list with reasons. It is yours, in full, whether or not you ever hire us to build anything.
Roadmap, tool selection and training are quoted separately and only when they’re needed. We don’t bundle them, because most clients only need the first one.
How an audit runs
Step 1 — we talk to the people doing the work
Not only the managers. The person who actually processes the invoices knows where the time goes, and it is rarely where the process diagram says. Half a day per function, usually.
Step 2 — we count
Volumes from your own systems where they exist, estimates where they don’t, clearly marked as such. A recommendation built on a guessed number should say so on its face.
Step 3 — we score and cost
Every candidate against the four criteria, then a build estimate for the survivors. Estimates come as ranges, because a single number at this stage is a guess wearing a suit.
Step 4 — we walk you through it and leave
A session with whoever holds the budget, then the document is yours. No pressure to proceed and no expiry on the pricing beyond the honest one — that model and platform costs move.
What our clients say
The businesses we’ve built for, in their own words.
★★★★★
“When I approached Abedin Tech with my land share selling plan, I wasn’t sure how it would work. But thanks to their precise strategy and powerful marketing, my business is now thriving. They truly understand their clients’ needs and go above and beyond.”
Owner, Richland Properties
Real Estate
★★★★★
“I approached Abedin Tech to develop my website with several specific functionalities. Their team delivered exactly what I envisioned, creating a beautifully designed website that met all my requirements. I highly recommend Abedin Tech.”
Rohit
Owner, Shop from China
★★★★★
“The decision to partner with Abedin Tech was the best decision we made. Our site looks great, our traffic is through the roof, and our sales are better than ever. Abedin Tech is the perfect digital partner that offers what is beyond your expectations!”
James Anderson
★★★★★
“We had an idea but no sense of direction. With each step of the way, Abedin Tech guided us and turned our vision into a beautiful website with functionality. The outcome is evident by the numbers!”
Isabella Scott
Find out which three things are worth doing
Tell us roughly how many people you have, what the business does, and which processes feel heaviest. We’ll come back with what an audit would cover and what it would cost — and if we think you’re too early for one, we’ll say that instead.
What does an AI consulting engagement actually deliver?
A written report, not a presentation: the processes we examined, what each currently costs in time, a score against volume, time per instance, cost of being wrong and data readiness, an estimated build and running cost for the ones worth doing, a suggested sequence, and an explicit list of ideas we think you should drop with the reason for each. It is yours in full whether or not you hire us to build anything.
How do you decide which AI projects are worth doing?
Four criteria, none of them about the technology. How often the process actually happens — six times a month is somebody’s afternoon, not a project. How long one instance really takes, including the interruption cost. What a wrong output costs, since high error cost triples the engineering around a build. And whether the data and rules already exist anywhere, because if they live in one person’s head the first phase is archaeology and should be priced as such.
Will you recommend building something even if we do not need it?
No, and the no-list is a standard part of the deliverable. We have completed audits whose recommendation was to automate nothing yet and fix a process or a data problem first. Saying so costs us a build in the short term and is the reason those clients came back.
Are you tied to particular AI vendors or platforms?
No. Tool selection compares what exists against what you would have to build, judged on total cost rather than sticker price, and includes the switching cost if a vendor changes its pricing. We also do not recommend a platform before we know what the work is, which is the wrong order and the most common mistake in this market.
How long does an AI opportunity audit take?
Usually a few days of fieldwork spread over two to three weeks, depending on how many functions are in scope and how available your people are. Roughly half a day per function talking to the people who actually do the work, then counting, scoring and costing, then a walkthrough with whoever holds the budget.
We are a small business. Is this only for large companies?
Small businesses often get more from it, because a single well-chosen automation is a larger share of their capacity. The audit scales to what is in scope, so a ten-person company is a smaller and cheaper piece of work than a two-hundred-person one. The thing that makes an audit premature is not size but having no repetitive process at meaningful volume.
What usually comes out of an audit
The builds most often recommended, so you can see what you’d be choosing between.
