Managed AI Agents

What agents do is measured, on quality, cost and escalations, and the agents are improved accordingly. An agent without monitoring is an experiment, not an operating asset.

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A woman in a blazer stands at the head of a workshop table and talks to four colleagues around it, two of them seated with laptops, a green notebook lying on the table.

What we look at

From a pilot to an operation you can rely on.

Every agent has metrics

Completed cases, quality of results, escalation rate and cost per case. The numbers show whether an agent meets its business case, not gut feeling.

Escalations are the most important signal

Where agents regularly hand over to people, there is either a gap case or a system problem. Both are evaluated and fixed, specifically rather than broadly.

Changes are safeguarded

New models, changed instructions or extended rights only go live after a regression check. An agent that worked yesterday should still work tomorrow.

What you receive

Four things that make agents dependable.

Quality & cost metrics

Per agent: completed cases, quality of results and cost per case, set against the business case.

Escalation analysis

Handovers to people evaluated systematically: close the gap cases, fix the system problems.

Continuous optimisation

Instructions, knowledge and tools of the agents improved on the basis of measurement.

Safeguarded changes

New models and prompts only go live after a regression check.

FAQ

Frequently asked questions about Managed AI Agents

How do you measure the quality of an agent?

Through defined test cases and samples in operation: was the case handled correctly, would a person have decided differently, was the escalation justified. The criteria come from the use case, not from the model.

Why do agents need their own monitoring?

Because their behaviour changes without anyone touching code: new model versions, a different data environment, new case types. Classic system monitoring sees none of that, while agent monitoring measures results.

What happens if an agent gets worse?

The measurement shows it early, as quality falls or escalations rise. Then it is improved specifically, through instructions, knowledge and tools, and the change is safeguarded by a regression check before it goes live.

Do we see the numbers ourselves?

Yes. Metrics per agent sit in the Leitstand, our agent control room, not in the engine room. Owners see performance, cost and trends, which is the basis for deciding which agents to expand.

Does this connect to governance?

Closely: monitoring supplies the evidence Agent Governance & Oversight requires, including logged actions, checked changes and documented escalations.

Case Studies

What comes after the plan.

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Dovista

68 %

Of all enquiries automated.

Other Operate services

Three more services in Operate

If Operate is not the right starting point for you, explore the other phases of the Agentic Growth Stack as well.

Explore Plan Services

Explore Build Services

Explore Automate Services

Managed HubSpot Platform

Ongoing operation of your HubSpot platform: further development, data maintenance, releases and a dedicated contact.

Managed Custom Software

Operation, maintenance and further development of your in-house software, including monitoring and security updates.

AI Enablement & Academy

So the system actually gets used: training, enablement and measured adoption instead of dead records in the CRM.

Let’s work together

The first step towards an agent-native company.

In the NATIVE Assessment we develop a clear target picture and a business case that holds up, in four to eight weeks. Fixed price, no open-ended day rates.

Rather talk first?

We get back to you personally.

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