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Run, Scale & EvolveAgentOps

Keep your agents and automations working as intended.

Once AI is live, the hard part is knowing it still does what it should. Roboyo runs your automations, low-code applications and agents as one estate under one operating model. We watch how they behave, not only whether they run, detect and contain drift, and keep improving them once they are stable.

Discuss what's in production See how it works

Where it goes wrong after go-live

An agent can be running and still be wrong.

Automations usually fail in ways people notice: a job stops, an error appears. An agent can keep running and produce output that looks right and isn't. Its behavior can shift when its model, instructions, data, tools or access change, or when people start using it differently. Until someone spots it, the agent keeps writing data, making decisions and sending messages. Waiting for an alert is not enough.

At the same time, automation, low-code and AI tools, often on different platforms, now depend on each other. When each is supported on its own, a failure between them leaves teams blaming each other.

AgentOps is designed for teams in one or more of these situations:

  • Running it is outgrowing the team.

    Agents or automations are live, or about to be, and your team lacks the time or skills to keep them healthy.

  • Governance exists on paper.

    You have AI policies, but they are not yet applied to the live systems day to day.

  • You've inherited someone else's build.

    Another provider or your own team built the portfolio, and now it needs to be stabilized and owned.

From support to operations

Keeping AI up is not the same as keeping it right.

A support service keeps software available: it watches uptime, takes tickets and fixes what breaks. That still matters. But an agent can be available, error-free and wrong, so the service has to check what it did as well as whether it ran. Governance sets the rules. Operations applies them in the live system every day.

  1. 01Agreed limits
  2. 02Running in production
  3. 03Behavior watched
  4. 04Drift detected
  5. 05Response and recovery
  6. 06Improvement
  7. 07Controls rechecked after change
Illustrative loop; the controls depend on the asset and its risk.

What gets checked

Whether it ran

Whether it did what it was meant and allowed to do

How problems surface

An alert or a user report

Signals that behavior is shifting, such as changes in outputs, tool use, guardrail triggers or hand-offs to people

What service levels measure

How fast tickets are resolved

How well the automations and agents themselves succeed

The result is an estate you can account for: what each asset is, who owns it, what it may do and what it actually did.

What you get

One operating model for everything you run.

A clear account of your estate

Every automation, application and agent is recorded with what it is, who owns it, whether it can be run safely and what service level applies. AI assets are classed by how they behave in production, not by what the vendor calls them, and get the controls their class needs. The assessment reports material risks only, and each finding is fixed, put under a control or planned for improvement.

Operations that watch behavior

Monitoring covers behavior as well as availability. When an agent starts to drift, the response is graduated: watch it more closely, add human review, restrict what it can do or contain it. Incidents, recurring problems and changes each follow a defined process, and a change to a model, prompt, data source, tool, permission or level of autonomy triggers a fresh check of controls.

Evidence and steady improvement

The service keeps a record of what each asset saw, what it decided, on whose authority it acted, what it did and what came of it. Every incident is recorded and kept, not just alerted. You review performance with us at operational, service and executive level, and once the estate is stable the work shifts to improving it.

How the service works

Start from what's live, or from what's about to launch.

There are two ways in. If assets are already live, we assess what's there and fix the highest-risk gaps first. If you're still building, the operating requirements are written next to the functional ones, so the asset can be run properly from its first day in production.

  1. 01

    Assess

    We establish what runs, who owns it, how healthy it is and where the material risks are. For each asset we agree how it can be operated: fully, with limits, after fixes, or not yet.

    OutputAn account of your estate and an agreed operating position for each asset.

  2. 02

    Take over and stabilize

    We learn how the estate runs today, agree how our work connects with your teams and tools, and check the arrangement works before you rely on it. Then we stabilize what matters most.

    OutputAssets in operation with named owners, defined controls and monitoring.

  3. 03

    Operate and improve

    We run the estate day to day: watching behavior, responding to incidents and rechecking controls after change. When something goes wrong, recovery includes working out what the asset already did, not just restarting it. Performance is reviewed with you on a regular cycle, and once the estate is stable the focus moves to improving it.

    OutputReported performance, a record of every incident and a plan for what to improve next.

Discuss what's in production

Find the right starting point

Nothing in production yet? Start with the build.

AgentOps fits once agents or automations are live, or about to be. If the workflow still needs to be found and built, start with Agentic FDE; AgentOps runs what it builds from the first go-live. If you want AI and agents built into applications you already use, explore the Agentic Application Launchpad. If you need controls designed into how your AI acts and what it can access from the start, explore Security by Design.

Practical questions

Takeover, scope, readiness, control and cost.

Do you only run what Roboyo built?

No. We also take over portfolios built by other providers or by your own teams. The takeover is a planned transition: we learn how the estate runs, check its quality and agree for each asset what we can commit to before you rely on us.

What can you operate?

Automations, low-code applications, chat tools and AI agents, including estates that span several platforms. The services we switch on depend on the kinds of assets you run, all under one operating model.

Do we need agents in production before we talk?

No. If you are still building, operating requirements can be set alongside the functional ones, so the asset is ready to run from its first day live.

How do control and accountability work?

Decisions stay with you. Each asset has a named owner and a defined scope of what it may do, and the service records what it did and on whose authority. Changes that could alter an asset's behavior trigger a fresh check of its controls.

How long does it take, and what does it cost?

That depends on what you run and the cover you need. We agree scope, coverage, service levels and commercial terms with you before the service starts.

Bring us what's already live.

Tell us what you run in production, who looks after it today and what happens when something goes wrong. We will help you work out where it stands and where to start.

Discuss what's in production