Service · AI Studio
How we work.
Three steps to an AI agent organisation: getting to know each other, pilot, roll-out and expansion. Without restructuring your organisation; the agents join the existing teams and tools.
01
Three steps.
Step 01
Getting to know each other
Identify potential together and define the first process. Free of charge, without obligation, usually a conversation of 30 to 60 minutes.
Step 02
Fixed-price pilot
Concept and build of the first agent team, connected to your systems. Two to four weeks, demo on the running system.
Step 03
Roll-out and expansion
Hand-over to the team, briefing, operation as a managed service, identification of further processes. Ongoing.
Step 04
Your effort
One contact person and data access. We do the rest.
02
Three layers. One solution.
Each layer builds on the next: a proven base, an individual top. The result is not a one-off that only works with us, but an architecture your team understands.
01 · Platform
The technical base on open software: agent runtime, session management, scheduling, connection to messengers such as Teams or Slack, several model providers.
02 · Core
Our extensions and your company knowledge: knowledge synchronisation across teams, security and isolation, cost control through token budgets, elementary company knowledge as the base.
03 · Team layer
Enrichment per department: team knowledge such as accounting entities or glossaries, team-specific agents and interfaces, own workflows and automations, team tools.
03
Agent teams instead of single agents.
Per task, workflow or department a team of specialists, coordinated by an orchestrator that distributes tasks and checks results, like a team lead. If a question crosses a boundary, the coordinator brings in the neighbouring team instead of someone calling a meeting.
- Specialised: finance, data analysis, customer service, product and engineering, operations, marketing, each with access to the matching systems.
- Orchestrated: agents work together on a project basis; results are cross-checked.
- Model-agnostic: we choose the suitable model per task, without vendor lock-in.
04
Who decides what.
find the anomaly → narrow down the cause → present proposal with evidence → assess and prioritise → decide → approve → implement → measure the effect
The highlighted steps rest with people. That is not a statement of intent but set through the granted permissions: every agent gets exactly the rights its task requires. How far it may go is a dial you set, in both directions, at any time.
05
Who is behind the AI Studio.
Christian Teichert
CEO and founder. More than two decades as a founder and entrepreneur. Built the AI agent organisation in-house before it became the offer. LinkedIn profile →
Frank Maschmeier
COO. Responsible for delivery and operations, from the first meeting to the running agent team at the client. LinkedIn profile →
Frequently asked
How we work: frequently asked.
Do we have to restructure our organisation?
No. The agents join the existing teams and tools. No new structure, no transformation programme, no additional tool for your staff.
What role does our IT team play?
It grants access and can take over monitoring if you want to operate yourself. For the pilot, a contact person from the business unit is enough.
Why model-agnostic?
Because models evolve quickly and differ in quality per task. We choose the suitable model per task and swap it when a better one is available, without touching your rule set.
More services
Fixed-price pilot · Operation and support · Data security and hosting · All use cases
Does this sound familiar?
In a first conversation we look at your processes together and sketch out where an agent team would make the biggest difference. Free of charge and without obligation.