AXOODREN Contact DE

AGENTIC
AI.

An agent is given a goal. And delivers the result.

Chatbots answer. An agent plans a sequence, queries your systems, decides within the set limits and delivers the result, without waiting for the next prompt. We build such agents where they really take work off the Mittelstand: in processes that people only handle today because systems do not talk to each other.

On the left a speech bubble with three dots, on the right a robot handing over a stamped document

What an agent takes over.

An agent is not a better chatbot. It is a digital co-worker for clearly defined tasks, with access to your systems and clear limits.

A robot checks a stack of invoices with a magnifying glass

Back office.

Check invoices, match them against order and delivery note, clarify discrepancies and prepare approvals. People only decide the exceptions.

A robot at a service counter hands over a document with a check mark

Service.

Understand enquiries, look things up in the ERP or CRM, deliver the answer with evidence, without forwarding. What the agent does not know for sure goes to a colleague with a proposal.

A robot with a torch repairs a blinking server rack at night

Operations.

Detect the fault, narrow down the cause, trigger the countermeasure, including ticket, notification and documentation. At night just as during the day.

How an agent works.

An agent is given a goal, not a click path. It breaks the task into steps, calls the necessary systems, checks intermediate results and gets approval where you have specified it. Every step is logged, traceable for the department and for audit.

Human-in-the-Loop is not a stopgap but a design decision: which decisions an agent makes alone and which a person approves, we define together beforehand.

agent · invoice-check #4821

  1. 1Goal received: check incoming invoice against purchase order
  2. 2Fetching order 88-2210 from ERP1 request · order found
  3. 3Comparing 12 line items
  4. 4Mismatch found: line 7 quantityordered 40 · invoiced 44
  5. 5Drafting clarification e-mail to supplier
  6. !Waiting for human approvalamount above your limit
  7. 6Approved · e-mail sent · payment on hold
  8. 7Case closed · logged for audit

How we proceed.

01

Select.

At the end you haveThe first use case with leverage, system access and approval logic, before a single line of code is written.

02

Build.

At the end there runsAn agent in test operation with real data, a log and approval steps.

03

Operate & scale.

At the end there worksThe agent in daily business, monitored, documented, extensible. The next one builds on the same foundation.

A robot points at a highlighted box in a flowchart

At the end you haveThe first use case with leverage, system access and approval logic, before a single line of code is written.

1 / 3

Walk the processes.

Where is work handed on, copied, queried today? We look where work gets left behind.

A scale weighs a stack of forms against a small gear

2 / 3

Assess the lever.

Effort, cost of errors, data access: what carries a business case, what is merely nice?

A robot hands over a document, a person applies the approval stamp

3 / 3

Define approvals.

What may the agent decide alone, where does a person decide? That is settled before anything is built.

A robot is assembled on a workbench, cables lead to three servers

At the end there runsAn agent in test operation with real data, a log and approval steps.

1 / 3

Connect access.

ERP, CRM, mail, interfaces, clean, logged and reversible at any time.

A robot ticks off a checklist, a person looks over its shoulder

2 / 3

Test operation with real data.

Every decision is recorded and checked by your people.

Documents run along a belt through a barrier, a person stops one of them

3 / 3

Build in control.

Approval steps exactly where they belong, not everywhere, not nowhere.

Three identical robots on a belt, the first is already working at a desk

At the end there worksThe agent in daily business, monitored, documented, extensible. The next one builds on the same foundation.

1 / 3

Monitor.

Every decision visible, costs in view, anomalies report themselves.

A robot turns dials, a curve rises on the screen

2 / 3

Improve.

Edge cases become rules, rules get better, in step with your feedback.

Two robots at the same power strip, one already working, the second being plugged in

3 / 3

Connect the next agent.

Same access, same rules, far less effort than for the first one.

Autonomous does not mean unsupervised.

A robot hand and a human hand hold a stamp together

Approvals where they matter.

Amounts, customer data, contract changes: together we define from which point a person decides. The agent prepares, the person approves.

A robot with a glass belly in which gears and a checklist are visible

Every decision traceable.

What the agent did, when and why, is in the log, for the department, audit and the EU AI Act. Cost limits and emergency stop included.

Which process should be the first?

Tell us where people only pass things on today, and we will tell you whether an agent can take that over.

FAQ.

What distinguishes an agent from a chatbot?

A chatbot answers a question. An agent is given a goal, breaks it into steps, accesses your systems, checks intermediate results and delivers the finished result, with a log. It works instead of answering.

Which processes are suitable to start with?

Recurring workflows with clear rules and a few exceptions, that run across several systems and whose success is measurable: invoice checking, service requests, master data maintenance, fault reports. That is exactly where an agent takes noticeable work off you right away.

What happens if the agent makes a mistake?

An agent may only do what we have defined beforehand, with approval thresholds, cost limits and an emergency stop. Every step is in the log and can be reversed. That is why every agent starts in test operation with real data before it makes decisions in daily business.

Do we need new IT for this?

No. Agents connect via interfaces to what you have: ERP, CRM, mail, ticket system. They run on your infrastructure or in the cloud of your choice; the data stays where it belongs.

How long does it take to get the first agent?

Selecting the first use case takes a few weeks, the first agent in test operation follows in weeks, not months, depending on interfaces and data. In the first conversation we give you an honest estimate for your case.