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Technologies

OpenAI integrations: artificial intelligence wired into your processes

The models behind ChatGPT, connected to your company's data and workflows — with realistic expectations.

OpenAI's models — the engine behind ChatGPT — can take over tasks that until yesterday required people exclusively: reading and classifying incoming documents, extracting data from invoices and contracts, answering customer questions from internal documentation, summarizing long conversations. We build these integrations end to end: connecting models via API to existing systems, grounding them in company data so answers are verifiable, and installing cost limits and human control where decisions matter. We also speak openly about the limits, because they exist: models can state falsehoods with confidence — which is why critical flows keep human validation — costs grow with volume unless designed carefully, and transmitted data must be handled under GDPR, anonymized where needed. AI delivers real value precisely when implemented with serious engineering rather than demo enthusiasm.

Let’s talk about your project

Message us on WhatsApp or send an email — you talk directly to a developer.

office@northdan.com · +40 752 070 247

What you get

Hours of repetitive work, eliminated

E-mail classification, document data extraction and summaries happen automatically — your team stays on decisions requiring judgment.

Answers grounded in your data

We connect the model to your documentation and databases — it answers from company sources with verifiable citations, not from imagination.

Costs and risks under control

Consumption limits, answer-quality monitoring and human validation on sensitive flows — AI with brakes, not blind trust.

Frequently asked questions

Which business processes are worth automating with AI today?

High-volume ones with moderate stakes per case: mail sorting, invoice data extraction, first-line customer replies, meeting summaries. There occasional errors are cheap to correct while the time savings are immediate and measurable.

Models can state falsehoods confidently — how do you manage that risk?

Through architecture, not hope: answers are grounded in company documents with source citations, critical flows keep human approval, and quality is measured continuously on real cases. The model proposes; the process verifies.

Does our data end up training OpenAI's models?

Not through the developer API — OpenAI’s official documentation states that data sent this way is not used to train its models, unlike the free browser version of ChatGPT. What remains to be configured is on your side: which personal fields are anonymized before transmission and who is allowed to query the assistant.