Get AI agents into production.
And keep them there, protected.

Most AI projects don’t fail on the model. They fail because no one will let the agent into production. We build the guardrails, the infrastructure and the operations that turn a pilot into a system. In your cloud or fully on-premises.

10

Working days to the readiness report

10+

Years of enterprise experience on the team

The problem

The pilot runs. Now what?

In almost every company we talk to, there is an AI prototype that impressed. And a list of reasons why it isn’t allowed into production.

These aren’t model problems. They’re engineering problems, and that’s exactly what we solve. We deliver the technical evidence your compliance team needs. Assessing it stays with them.

Access to too much

The agent can reach systems and data that are none of its business.

No traceability

No one can reconstruct why it decided what it decided.

No quality watchdog

Nothing notices when it gets worse after three months.

Uncapped cost

No one knows what an agent costs per month until the invoice arrives.

Anatomy of a production system

How an agent runs in production, under control, with us

A prototype is the agent alone. A production system is everything around it: control over who may do what, the vetted path to your systems, the human at the edges, the gap-free log and the continuous measurement. That’s what we build.

INFRASTRUCTURECloud · Knowledge access · Version control · Deployment with rollbackevery production version knownAUDIT LOGInput · Role · Tool · Output · Timestamp · Model version · immutableHumanconfirms at thresholdEVALUATION & MONITORINGEvidenceDeviation · Costmeasured continuously, alerts us firstRequestTrigger / userRBACCheck rolewhich permissionsAgentplans · acts · checksevery step boundedGATEWAYvalidates & logsrollback-capableYour systemsERP · CRMDMS · Legacyno direct accessGUARDRAILSescalatesmeasures outputs

Six layers of control around a model. That’s exactly the difference between a pilot and a system that gets approved.

Services

Eight areas that turn an AI prototype into a production system

Focus industries

Where AI systems are under scrutiny

Industries where a working prototype isn’t enough, because approval, evidence and operation are what count.

Testing & Audit

Public Sector

Medical Technology

Automotive

Legal Tech

The more regulated an industry, the less a working prototype is enough. That’s exactly where we start.

Technologies

The stack beneath operations

AI & Agents

LLMsRAGLangChainMCPDocument AIEvaluation Frameworks

Cloud & Infrastructure

AWSGoogle CloudAzureDockerKubernetesTerraform

Observability & Governance

OpenTelemetryPrometheusGrafanaAudit-LoggingRBAC

Backend & Data

PythonFastAPIPostgreSQLVector StoresETL
How we work

We’re a small, experienced team. That’s the point.

You don’t hand your production systems to anyone on blind trust, and rightly so. So we’re open about how we work: senior, hands-on, no layers in between. You get the people who build the system, not their sales team.

And you get nothing you can’t walk away from.

The two who pitch also build

No junior with a template, no ticket passed along. You work directly with the engineers who develop and operate the system.

No lock-in

Code, prompts and runbooks are yours. We build so that your team or another provider can take over at any time. No dependency.

Your environment, your data

Operated in your cloud or on-premises if you prefer, data kept in the EU, processing under GDPR. No data leaking into systems you don’t know.

Verifiable, not asserted

We write down nothing we can’t back up in conversation.

Contact

Let’s talk

Every system in production starts with a conversation. Tell us where your pilot stands today.

Emir J. Adler, Managing Director of Systemator GmbH

Emir J. Adler

Managing Director

Kemal Cholovich, Founding Partner at Systemator GmbH

Kemal Cholovich

Founding Partner

Your contacts

Software engineers with over 10 years of experience in enterprise systems. We do the work ourselves, from architecture to operations.

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