I sell the part you can measure. Not the part you cannot.

1. Yes

   An MSc in Computer Science with an AI focus — machine learning, natural language processing and computer vision — from Can Tho University. Eight years of software development before that, mostly TypeScript and systems that actually run.

2. Not yet

   None of my AI work runs in a customer's product today. The machine-learning side is applied research in progress, and I am moving it from coursework toward real work. I will not sell you a list of AI customers, because that list does not exist yet.

3. So what I am selling

   Integration, measurement and operation. Putting a model into your actual process, measuring how right it is on your actual data, measuring what each run costs, then handing it over so you operate it. Not a pre-trained model, not fine-tuning a foundation model, not AI strategy with no build attached.

• Accuracy only means something on your data

  An accuracy figure measured on somebody else's dataset does not transfer to yours — different industry, different way of writing, different noise. I build the evaluation set from your own samples, run it before handover, and report that number.

• Cost per answer is not a constant

  It depends on the real length of your sentences, how many calls you make a day, and what the model costs on the day it runs. I count on your own sentences rather than estimating from intuition — and I write the assumptions into the quote.

• “It did not reach the bar” is a valid result

  If the evaluation set comes out low, you should know that before you order the next package. A two-week measurement that answers the question is cheaper than a six-month build that reveals it was never going to work.

Questions about AI

Have you shipped AI for a client?

Not in productised form. My machine-learning work is applied research in progress — an MSc with an ML/NLP/CV focus — and I am actively moving it from coursework into real work. I have no AI client list to put on this page and I will not invent one. That is exactly why the first package is a measurement rather than a build.

Where should I start?

With a measurement, not a project. The entry package is roughly two weeks and ends with numbers on your own data: accuracy, cost per run, and what the system gets wrong. You pay for the measurement before committing to anything further.

What will it cost per month to run?

I will not give you a number from the sky. It depends on your real sentence lengths, your daily call volume and the model's price on the day it runs — so I count on your own sentences and write the assumptions into the quote. Every AI quote I produce carries an estimated run cost line.

Does my data get sent anywhere?

No. I do not use your data to train somebody else's model, including my own. That is a boundary I write into the scope, and I think it belongs in writing.

Do you do computer vision — product quality inspection from images?

I do not sell it as a service. Image inspection needs a conveyor, controlled lighting and a real volume of defect images in the plant — which a small business here usually does not have. I describe that as a capability, not something you can order.

Will this automate everything?

No, and I do not promise it will. At the scale of a small business, most of the time goes into data that disagrees with itself rather than into the model — a process where you cannot produce clean data will produce poor results, however good the model is.