Services

AI agents that carry real workflows

Autonomous software workers for repetitive knowledge work — with guardrails your auditors will accept.

An AI agent is a step beyond a chatbot: instead of only answering questions, it executes work — reading incoming invoices, drafting replies, updating your CRM, escalating exceptions to a human. We are a Romanian software company building agents on top of the large language models, wired into the systems you already run. The engineering that matters is rarely the model itself; it is the guardrails: what the agent may touch, what it must log, and when it has to stop and ask a person. Working with us feels like working with a local team — overlapping European business hours, contracts and invoices under EU law, English throughout — while the intellectual property and every line of code stay yours from day one.

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office@northdan.com · +40 752 070 247

What you get

Autonomy with guardrails

Every agent gets an explicit permission boundary, an audit log and a human-escalation path — so automation never becomes an unaccountable black box.

Wired into your real systems

Agents read and write through the APIs of your ERP, CRM, inbox or ticketing tool — they work inside your stack, not in a demo sandbox.

ROI measured, not promised

We start from one workflow with a measurable cost — hours spent, error rate — and prove the saving before expanding the agent’s scope.

Where AI agents earn their keep today

The agents that pay for themselves are narrow ones. An inbox agent that reads supplier invoices, extracts the lines, matches them against purchase orders and posts only the clean ones. A first-line support agent that resolves password resets and order lookups, then escalates everything else with a written summary attached. A sales agent that enriches inbound leads, scores them against your criteria and books the meeting. Each owns a bounded task with a measurable before-and-after.

What we decline to build is the agent with unlimited scope and unlimited permissions. Every deployment we ship names the systems the agent may write to, logs each action it takes with the reasoning attached, and defines the confidence threshold below which a person decides instead. That structure is the difference between a demo that impresses a board and a system your finance team is willing to leave running overnight.

Frequently asked questions

How is an AI agent different from a chatbot?

A chatbot converses; an agent completes tasks. It can look up an order, issue a credit note in your ERP and email the customer — a conversation is just its interface, not its job.

What happens when the agent is unsure?

It stops and escalates. We design explicit confidence thresholds: routine cases run automatically, ambiguous ones land in a human review queue with the agent’s reasoning attached.

Can we run this without sending data to US model providers?

Yes — we can deploy open-weight models in your EU cloud or on-premises when data residency rules require it, and we document the data flow for your DPO either way.