Agentic
Intelligence
Teams
Specialised AI agents that work as a team – orchestrated, equipped with tools and with humans in the loop.
From now on doable. We build Agentic Intelligence Teams – AI agents that research, decide and act.
Specialised AI agents that work as a team – orchestrated, equipped with tools and with humans in the loop.
Where does AI really pay off? Prioritised by impact, effort and risk.
Agents with access to your systems: CRM, ERP, knowledge, mail – via APIs and MCP.
From whiteboard to working prototype with your real data.
Recurring knowledge work that gets itself done – traceable and auditable.
Teams that understand AI, steer it and keep building on their own.
Guardrails, evaluations and monitoring that keep agents reliable.
Specialised agents take on roles, check each other’s work and run in parallel. An orchestrator distributes the work. And you sign off.
Request in, priced proposal out.
Understand, sort and answer tickets.
Read hundreds of documents, flag the risks.
Matched against order, contract and delivery.
Analyse accounts, spot signals, write briefings.
Ask your entire company knowledge, with sources.
Pull the numbers, interpret them, send the report.
Match profiles against requirements, fair and reasoned.
Tell us what’s impossible for you.
Let’s go ↗Use-case sprint with your teams. We find the spots where agents make a real difference.
Prototype with real data and real tools. Measurable, testable, ready to show.
Operations, monitoring and enablement, so the prototype becomes a member of the team.
Several specialised AI agents working on one task together. Each agent has a role, such as research, analysis, writing or review. An orchestrator distributes the work, and a human approves the result.
A chatbot answers. An agent acts: it uses tools such as your CRM, ERP, knowledge base or email, completes several steps on its own and submits the result for approval.
The systems you grant access to, for example CRM, ERP, knowledge bases, email and calendar. They are connected via APIs and the Model Context Protocol (MCP).
Three steps. In a use-case sprint we work with your teams to find where agents make a real difference. Then we build a prototype with real data and tools. After that it goes into production, with monitoring and enablement.
Yes. Agents work within guardrails, are continuously evaluated and monitored, and a human approves the results. This includes classification under the EU AI Act.
Studio Artifique is a service of Deal Engine GmbH, based in Potsdam, Germany. The team builds AI agents for companies and supports them from strategy to production.
What’s impossible for you?
hallo@artifique.studio ↗