Direct definition: We create systems of specialized AI agents coordinating research, decisions and actions within marketing and business processes. Every agent has a defined role, context, tools, permissions, quality criteria and oversight.
The challenge
Autonomy without design multiplies risk. A reliable agentic system divides work, controls sources and actions, records what happened and escalates exceptions to people. We select processes where outcomes can be verified and coordination creates genuine advantage.
How we work
- Process decomposition into tasks, decisions and control points.
- Design of agents, memory, tools, permissions and evaluations.
- Pilot, observability, oversight, integration and progressive scale.
Application example
A campaign preparation system includes a research agent, an audience agent and an evidence-control agent. They share an approved knowledge base, generate a proposal and flag contradictions. The owner decides the concept and authorizes activation. Logs reveal which source and reasoning supported each recommendation.
How it is measured
- Correct task resolution
- Human intervention and exceptions
- Time and cost per process
- Traceability and compliance
Frequently asked questions
How is it different from a chatbot?
An agentic system uses tools, coordinates tasks and can execute controlled actions.
Can it connect to our systems?
Yes, through integrations and permissions limited to the use case.