Codify rules
Stable business rules are explicitly documented in the workflow and executed reliably.
AI automation for business
AI automation with the simplest suitable architecture.
Each process step gets the logic it needs: fixed rules, controlled AI interpretation or dynamic tool use.
The real task
Solve each process step with the simplest suitable logic and limit probabilistic components to the places where they add real value.
Use AI selectively
Classification, extraction and open-ended interpretation are integrated into the workflow as clearly scoped steps.
Earn autonomy
Start with assistants and copilots, build trust and data, and automate only where the benefits and tolerance for error justify it.
What you receive
Automation Architecture + Implementation Sprint
Define the target process, system boundaries and the simplest suitable architecture, with the option to implement a scoped first solution directly.
Target Workflow
Map inputs, AI steps, deterministic rules, approvals, exceptions and documented results as one system.
Architecture Decision
Choose between traditional automation, an AI workflow, an agentic substep and an agent based on the target process.
Control & Escalation
Define confidence thresholds, human review, error handling and actions that can be responsibly delegated.
Working First Version
When the scope is suitable, the simple workflow is built, tested and handed over as a usable first version.
Case Studies
A workflow in production with measured impact.
B2B event organizer · Production system
> 1,000 hoursFirst-level support time saved across more than 12,000 chats and 50,000 answered messages at 16 events.
Choose the Automation Architecture + Implementation Sprint when
- You want to improve a recurring email, document or knowledge process
- The workflow is largely understood and includes individual interpretation steps
- Reliability and maintainability have clear requirements
- The architecture can combine rules, AI steps and human approvals
What you will have afterward
- An improved target process with a measurable outcome
- A clear separation of rules, AI steps and human decisions
- An architecture with defined quality and operational requirements
- An actionable workflow with appropriate controls and approvals
Our methodology
Proven frameworks for a viable automation architecture.
Deterministic vs. Probabilistic
Assigns fixed rules or flexible AI interpretation to each process step.
Workflow vs. Agent
Clarifies whether the workflow is fixed or requires dynamic planning.
Assistants → Copilots → Autopilots → Agents
Chooses the lowest level of autonomy sufficient for the desired outcome.
Start augmented
Starts with human decision authority and gathers evidence for further automation.
Start simple, stay simple
Limits architectural and operational complexity to what the value justifies.
Frequently asked questions
Quick answers.
When does a process need an agent?
An agent makes sense when the path to the outcome must be chosen dynamically and different tools or steps are used according to the situation.
Can no-code be production-ready?
Production readiness depends on quality, error handling, monitoring, volume, maintainability and cost. Depending on the system, no-code can also meet these requirements.
Can a rule-based solution be enough?
Yes. Stable decision rules can often deliver the desired outcome more reliably and at a lower cost than a probabilistic step.
Get in touch
Match each process step to the right logic.
Outline the inputs, desired outcome, typical exceptions and current manual decisions. We will assess the simplest suitable architecture.