Build, coordinate and operate agents.
Agent Studio, Orchestrator and Mission Control connect models, knowledge, tools, workflows, approvals and execution surfaces inside one agentic platform.
Explore AI AgentsAbout Createting
We build infrastructure for AI systems that are allowed to act.
Models can already write, reason, speak and operate software. The harder problem begins when those capabilities touch real company data, tools, customers and decisions. Createting is building the operating layer around that work: context, execution, authority, orchestration and evidence.
The goal is not maximum autonomy. It is useful autonomy inside an architecture a company can understand, constrain and improve.
CompanyCreateting Platforms UG
Location95028 Hof
Represented byCanberk Gencay
Contactinfo@createting.com
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Why this company exists
AI stops being a demo when it can change an external system.
A useful business agent needs more than a prompt and a model. It needs the right context, bounded tools, state that survives a single turn, a way to ask for approval, a reliable execution path and evidence that the intended outcome actually happened.
That is why Createting is being built as a platform plus an implementation and infrastructure layer rather than as another isolated chatbot or workflow template.
Product principles
Mechanisms before adjectives.
These principles shape both the platform and how we approach customer work. They also define what we should be willing to show publicly.
01Start with the workflow.
Choose deterministic automation, an agent, a governed mission or a hybrid because the work requires it—not because one architecture sounds more advanced.
02Authority follows the action.
A read, a refund and a contract change should not inherit the same level of autonomy merely because one agent can technically request all three.
03One runtime, bounded capabilities.
Voice, browser, tools, knowledge and delegated workers should share the same operating controls instead of becoming disconnected automation islands.
04Evidence before expansion.
Scale what produces a measurable outcome under explicit constraints. Do not turn a promising demo into a broad deployment before the failure modes are understood.
05Architecture includes economics.
Model choice, routing, context, infrastructure and deployment shape cost as much as the application layer does.
06Say less. Prove more.
Benchmarks, product state and deployment boundaries should be distinguishable from targets, configured examples and future work.
What Createting is building
One company. Three connected layers.
Design the operating model before scaling it.
Map high-value workflows, decide where AI should act, define integrations and authority boundaries, and scope a controlled pilot around measurable evidence.
Explore ConsultingRun each workload on the right model and deployment layer.
Evaluate API, hybrid, dedicated and private options around capability, data, economics and operational requirements. Fine-tuning is used when evaluation shows it is justified.
Explore InfrastructureHow we work
Start narrow. Learn from real execution.
A smaller, measurable workflow usually produces more useful evidence than a large “AI transformation” program that cannot isolate what worked.
01
Map the process
Outcome, actors, systems, variability and current failure cost.
02
Choose the operating model
Workflow, agent, mission or hybrid—plus the capability and model requirements.
03
Define authority
Data access, tools, approvals, denied actions, escalation and evidence.
04
Run a controlled pilot
Measure the actual workflow under explicit validation criteria and operational safeguards.
05
Scale or stop
Expand what creates measurable leverage; reject weak economics or unreliable behavior.
A note on product status
We separate architecture direction from deployment evidence.
Createting is actively developing and hardening a broad agent runtime. A feature existing in the product architecture is not automatically proof that every deployment pattern is production-validated. Public claims should stay tied to current product behavior, completed testing and the configured environment.
Explore the work
See how the platform turns those principles into an operating system for agents.
Or start with one workflow and determine whether it should be automated, agentic, mission-driven or hybrid.
