AI Solutions

CX Solutions

AI Solutions that move safely into action: CreaLog combines AI models, company knowledge and existing systems into controllable solutions ready for productive use – in the cloud, on-premises or hybrid.

Discover the architecture

Trusted AI platform

Made in Germany

Cloud / on-prem / hybrid

Operation

CreaLog offers a modular platform for building, integrating and operating AI agents. Prompt-based agents can be connected to company knowledge, MCP tools, backend systems and communication channels – technology-neutral and suited to cloud, on-premises or hybrid scenarios.

An AI agent that answers impresses. An AI agent that acts needs a solid foundation

Models, knowledge, tools, processes and operation have to work together. The whole process and a sound architecture matter more than technological ideology.

Our platform brings these building blocks together into a sound architecture. The result is not an isolated FAQ bot but AI agents that use information, carry out defined tasks and fit into existing processes.

The CreaLog platform as an architecture

The platform does not merely connect AI components; it governs which information is used and which actions are carried out. Governance is not the bottom layer but a connecting level above all areas.

Interaction – voice, chat, digital applications, assistance
Orchestration – dialogue control, process logic, context
AI stack – rules, RAG, agentic AI
Integration – APIs, tools, MCP, business systems
Governance and operations – roles, logging, monitoring, fallbacks

A hybrid AI stack

Not every process needs the same AI. We decide architecturally, not ideologically.

Rules

Stable and auditable

For clear, critical workflows with predictable, verifiable behaviour.

RAG

Knowledge-driven

Context-based answers from approved company sources.

Agentic AI / MCP

Capable of action

Controlled actions in connected systems via defined interfaces.

MCP-native integration for knowledge, tools and actions.

MCP connects AI agents to approved knowledge resources, data sources, tools and backend functions. Defined interfaces are the basis for controllable access and traceable actions.

Provide knowledge · release tools · connect systems · document results

Create agents by prompt. Secure processes by workflow.

The role, behaviour and tasks of an AI agent are defined by prompt. Rules, MCP tools, routing and workflows cover the steps where clear sequences, approvals or unambiguous results matter.

The core process

Provide knowledge, reach systems in a controlled way

Identify
Recognise the enquiry, the process and the systems needed.
Read
Retrieve relevant data and knowledge sources deliberately.
Validate
Check rules, rights and plausibility.
Act
Carry out approved actions safely.
Evidence
Log sources, tool calls and results.

Governance is not an add-on feature but architecture

AI that acts needs clear responsibilities and verifiable points of intervention. Governance is therefore not added afterwards but anchored in the platform, the integrations and the operation.

Roles and permissions

Who may use which information and trigger which action is defined.

Approvals and four-eyes principle

Critical actions run through controlled approvals.

Logging and audit

Decisions, sources and tool calls remain traceable.

Versioning and fallback rules

Defined fallbacks when a step cannot be carried out safely.

Platform, integration and operation from one source.

AI components, communication and backend systems are connected on one shared basis. Service development, integration and operation mesh together.

The modular architecture integrates into existing system landscapes and can be laid out for cloud, on-premises or hybrid scenarios.

Our own platform · open choice of technology · integration of complex systems · support across the entire lifecycle

Data sovereignty is an architectural decision.

Cloud, on-premises or hybrid: data flows, model access and operating models are shaped to suit the deployment scenario.

Depending on requirements, local models, cloud services or combined setups can be used. Rights and roles, approvals, logging, monitoring and fallbacks are built into the platform, the integration and the operation from the outset.

Selectable models · controllable data flows · controlled system access · traceable actions

From MVP to scale