ETG SOFT

AI Integration

Automate document reading, customer replies or content tagging with AI connected to the software you already use.

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What’s included

  • Use-case and feasibility review
  • Large language model (LLM) integration
  • Search over company documents (RAG)
  • Extracting data from documents and forms
  • Support and sales assistants
  • Cost, privacy and accuracy checks

Technologies we use: Claude API, OpenAI API, Vektör arama

We set up AI to take a task off someone’s desk

The measure of an AI project is how many hours of repetitive work it takes off someone’s week. Reading invoices into the accounting system, sorting incoming email by topic, drafting product descriptions or answering questions from internal documentation are typical examples.

Integrated with care

At the outset we agree what data is sent to the model provider, whether it is retained, and how that fits GDPR and Turkish KVKK rules. For critical actions the model’s output goes through human approval, and accuracy is measured on sample data before launch.

How we work

  1. We listen first

    Goals, users and budget come first. The scope is agreed in a written plan.

  2. Then we build

    Design and development run side by side. You see a working build after every sprint.

  3. We grow it live

    After testing we launch, then keep watching speed, search and security.

Frequently asked questions

Will our data be used to train the model?

Business APIs generally don’t train on customer data, but we review the chosen provider’s terms with you at the start and share them in writing.

Can a model run on our own servers?

Where it makes sense, open-source models can run on your infrastructure. We compare hardware cost and accuracy during analysis.

How is the cost calculated?

Development is priced as a project; model usage adds a per-request cost. We estimate the monthly usage cost from sample data and include it in the proposal.

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