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VistulaCode

AI FOR DAILY BUSINESS TASKS

Read documents and check images with AI

Delivery notes and product checks should not hold up the rest of the day's work. We build tools that read scans, capture packaging labels or flag visible defects for staff review. Tests on your documents and photos, including poor lighting and unfamiliar layouts, show which checks can be automated and where people are still needed.

Discuss your taskHow we work
AI-generated illustration of Michał reviewing supplier and product data at a workstationAI AT WORK

Example: reading a scanned delivery note

  1. Delivery-note scan
  2. AI reads item codes and quantities
  3. Staff check unclear entries

Less retyping from scanned documents, with unclear details marked for staff to check.

AI-generated illustration

What you get

These are possible parts of a full project. The audit identifies what you need, a separately priced pilot checks the value, and you decide on implementation after seeing the results. See what each stage includes.

  • More time for checks that need a person

    AI performs the first check and sends uncertain results to staff. Testing establishes which cases it can handle.

  • Details ready for your systems

    Document fields such as item codes and quantities are collected in an agreed format, reducing retyping.

  • Know where checks are still needed

    See missed defects, false alarms and incorrect fields separately. Your team can judge the value and where human review remains necessary.

  • A setup that fits your site

    Processing can run in the cloud, on your servers or on suitable local devices, depending on internet access and data rules.

What we can set up

We agree which of these tasks your project needs before quoting the work.

  • Sort images

    Assign images to agreed categories so staff can find and review the right items.

  • Find and count items

    Locate products, parts or features in images and video frames.

  • Mark the affected area

    Outline a defect or object so its position and area can be measured.

  • Read scans and forms

    Extract fields and tables from invoices, delivery notes and forms. Handwriting is included only where tests show it can be read reliably enough.

  • Flag visible defects

    Identify possible defects on production or packing lines and send uncertain cases to an operator.

  • Prepare and label photos

    Agree what each image shows and check the labels, so the model learns from useful examples.

Where this could make a difference

Possible applications, not completed client projects or promised results.

  • Check product surfaces

    Flag possible scratches, dents or contamination on manufactured parts for an operator to review.

  • Read supplier delivery notes

    Collect item codes and quantities from different document layouts, flagging uncertain fields for staff to check.

  • Read packaging labels

    Capture printed labels and serial numbers from photos to reduce manual typing when goods arrive.

How a project runs

We agree the task, test it with your staff and review the results before putting it into daily use.

Audit, pilot and full build

  1. Step 1: Collect real examples

    Gather documents and photos, including difficult cases, and agree what a correct result looks like.

  2. Step 2: Test a first version

    Measure which fields or image checks work and where the tool makes mistakes.

  3. Step 3: Improve weak areas

    Add targeted examples for the document layouts, defects or lighting conditions that cause errors.

  4. Step 4: Launch with staff review

    Agree which cases require review and track errors as new documents or images arrive.

What to check before starting

  • Automotive imaging, vehicle media and vehicle inspection projects are outside this service.
  • Medical or diagnostic work requires qualified clinical partners and an agreed regulatory and safety plan before it begins.
  • Accuracy is measured on examples kept separate from training. We cannot promise a result before seeing your images and documents.
Technical details for your IT team

Tools are chosen for your existing systems and project requirements. You do not need to choose these before discussing the business task.

  • Python
  • PyTorch
  • Hugging Face · Transformers, Datasets, PEFT
  • Docker
  • Cloud GPUs
  • REST APIs
  • Edge runtimes · e.g. ONNX Runtime, chosen per deviceoptional

Common questions

How many images do we need?

We need examples of the document layouts, product conditions and difficult cases the tool will encounter. The initial review identifies gaps and what needs to be collected before a pilot.

Can it run at our warehouse or packing line?

Often, yes. We check the camera, local device and available connection, then test speed and accuracy on the proposed equipment.

What if images contain personal information?

We agree how to handle it before you share data. Depending on the task, this can include processing in your own systems, removing identifying details and limiting how long images are kept.

Related tasks we can help with

AI-generated illustration of Michał showing an AI-drafted customer reply to a colleagueAI AT WORK

Check the results before staff rely on AI

  1. Choose real work examples
  2. Check AI results against correct answers
  3. Your team decides whether to launch

Find incorrect answers and missing information during testing, before the tool enters daily use.

AI-generated illustration

CHECK THE BUSINESS CASE

Will this save your team enough work?

We agree how to measure time spent, errors and running costs. The pilot gives you evidence for the decision about a full build.

See how we test the idea

LET'S TALK ABOUT YOUR BUSINESS

What would your team do with more time?

In a 20-minute call, tell us what your team types, copies or searches for every day, and what those hours could be used for instead. We'll explore where AI could help and what we need to check.

Let's talk about your business

20 minutes to explore what takes up your team's time