Multi-Agent Systems
Turn your processes into teams of specialised AI agents that can research, analyse, produce and execute tasks together.
Specialised agents working as a team
A multi-agent system divides a process among several agents, each with a specific role.
Rather than asking a single AI to do everything, we design teams that can collaborate, share information, check results and involve a human when needed.
Automate more complex processes
Multi-agent systems are particularly suited to workflows that require multiple steps, areas of expertise or intermediate checks.
Examples
Marketing & content
Coordinator → Researcher → Writer → Channel Adapter → Reviewer
To research topics, produce content, adapt it for multiple channels and check it before publication.
Audits & analysis
Audit Coordinator → Technical Agents → Content Agents → Analyst → Report Generator
To divide an audit among specialists, consolidate the findings and produce a final report.
Monitoring & research
Research Agent → Source Validator → Analyst → Summary Agent
To monitor a topic, select relevant information and produce actionable summaries.
Internal processes
Intake Agent → Specialist Agents → Reviewer → Human Approval
To handle internal requests, automate selected steps and retain human approval for important decisions.
A system tailored to your processes
We do not aim to add agents everywhere.
We start by understanding your current process, identifying the steps that can realistically be automated and determining where human involvement is still needed.
We then define:
- the roles of the different agents;
- the information they can access;
- their interactions;
- validation rules;
- human checkpoints;
- the tools and systems they need to interact with.
From idea to operational system
We can support you from identifying a first use case through to designing and implementing the multi-agent system.
The goal is to create useful, controllable automations tailored to the way you work.