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AI Consulting · Istanbul

AI Consulting for Istanbul businesses

You can tell how far an assessment method will bend by looking at where its paper comes from. Where a reader machine does the marking, a layout change starts in procurement: a new batch has to be printed to the tolerance that machine accepts, and the exam calendar waits on the delivery. That dependency is where AI consulting in Istanbul begins for us. In the reading tool we wrote for Vipkurum, a layout revision becomes an adjustment on the Python side rather than a line on an order.

AI Consulting — Istanbul

If you repeat one method in many places, the cost of changing that method becomes visible as the scale grows. The work closest to this scale is Vipkurum's optical reading tool. Say where it does not reach: it was written for exam assessment, and we have nothing to show on contract extraction, invoice field capture or identity document checks. No language model does the reading. Underneath, Python and OpenCV run the image analysis, Node.js calls the service, and the exam record is written to MySQL on the Laravel side.

  • Marks are pulled off the image of the form with OpenCV, so the reading belongs to a software layer that can be called rather than to a device's optics.
  • When a new form layout arrives the adaptation is made in Python, and no reader hardware or machine-specific paper joins the purchase list.
  • What we do not promise is written down too: handwriting analysis, free-text scoring and identity verification fall outside this scope.

Why Algoriel

  • The image does the reading

    Vipkurum reads optical form marks with OpenCV from the image of the sheet, not through the optics of a reader appliance.

  • Cropping apart from judgement

    Image processing decides where a question begins and ends; the language model only binds the answer to it. The two jobs never mix.

  • Model output lands in a record

    Vipkurum writes the answer key into the cropped question's own record instead of keeping it as a separate document.

  • A person has the last word

    At Tahlil.com the model drafts the reading and a doctor approves what reaches the patient; an unapproved reading never appears on screen.

What we build

AI Consulting
  • Where no model is needed

    Marks on an answer sheet are read from the form image itself; the threshold that decides whether a bubble counts as filled sits in the code, and no language model runs in that step.

  • Splitting the job in two

    Computer vision sets the question boundaries; a language model then ties each answer in the key to its question. Cropping accuracy never rests on a model's interpretation.

  • Removing the hardware step

    Marking stops depending on a reader device; when the form layout changes, we adjust the reading service in software instead of ordering new hardware or device-specific forms.

  • Turning existing material into a pool

    A booklet page is split into individual questions, the answer key is written onto each question's own record, and the questions already on hand become the pattern for new ones.

  • Tying the output to a person

    At Tahlil.com AI prepares the first reading, a specialist physician writes and approves the interpretation, and responsibility for the text that reaches the patient stays with the physician who signed it.

  • Queueing the generation

    In Secretum text and images come out of two separate generation paths; image generation is not instant, so that work goes onto a queue, and the finished file is stored once instead of being regenerated in the feed. Secretum is the product we are building now.

Work like this

AI Consulting · Case study

Vipkurum optical reading — a layout revision lands in code, not on a purchase list

The reading tool we wrote for Vipkurum's education platform. Marks come off the image of the form rather than through a reader's optics; the job belongs to an image analysis layer standing on Python and OpenCV. The gain shows up in how the system adapts: when a layout changes mid-term, the adjustment is written in code, and no machine-specific paper order or delivery wait enters the picture. Forms are uploaded through the browser, the reading service is called over Node.js, and the result is written to a MySQL record on the Laravel side. The boundary: this tool was written for exam assessment, not general document extraction.

Read the case study →

Working with Istanbul teams, remotely

We have no office, so work for this city runs remotely and we do not offer on-site support. What was done, and why it was done that way, stays in writing. The project pages mark which builds came out of a partnership.

  • The first release ships as a working piece; extras follow later.
  • Every client we know of is in Turkey.
  • Decisions stay in writing; progress shows in working screens.

Frequently asked

  • Our optical reader works. Why move the reading into software?

    Even a working machine carries a constraint: the paper it can read is printed to its own tolerance. Change the layout and you meet a print order first and a lead time second. Move the reading into software and that order reverses: a layout change becomes an adaptation.

  • We expected a language model under the heading of AI consulting. Why image processing?

    Because the problem is not reading, it is where the decision is made. Measuring where a mark sits belongs to image processing; handing that measurement to a model's interpretation would make the result unsteady. We use language models elsewhere in the portfolio, matching questions to their answer key.

  • Our form layout changes every term. Is each change a fresh project?

    No. A new layout is handled by an adjustment on the Python side, and the same flow runs afterwards. That is the promise, and not an install that recognises any layout on its own.

  • How does this attach to the system we already run?

    The reading sits as a service and is called over Node.js; the record layer on the Laravel side writes the result into MySQL. Because that call is the join, the reading can sit apart from wherever the record is kept.

Let us look at which step needs a model and which one needs computer vision.