01
AI is added to a process that was not designed for AI.
AI hangs as a loose step off an existing process, without the information and decision flows being reworked.
Route 01 · Design — Operational AI architecture
What should a process look like before AI can reliably take part?
AI becomes reliable only when process design, data flows, decision points, release moments and roles fit together. Pientro designs this operational foundation and sets out where AI proposes, where people review and at which moments an outcome is formally released — as workable AI flows inside existing processes.
Conversation
A substantive conversation with a senior practitioner about your operational AI challenge.
Discuss your AI challengeSignals
When does this become relevant?
- 01
Processes have not yet been designed for AI.
- 02
Multiple colleagues or systems take decisions.
- 03
Decision points are not clearly defined.
- 04
Data comes from multiple sources and systems.
- 05
Release or control is missing in the process.
- 06
AI output needs to become a reliable part of the process.
Friction
What usually goes wrong?
02
Roles and responsibilities are unclear.
It is not explicit who proposes, who reviews and who formally releases.
03
Decision points are missing.
There is no defined moment at which an outcome is tested or moved on to the next step.
04
Exceptions are not handled.
The design ignores deviations, edge cases or intentional human intervention.
Approach
What does Pientro do?
Pientro maps data flows, process flows, source systems and manual steps, and designs where AI proposes, where people review and at which moments an outcome is formally released. Roles and AI workflows are placed so the process stays controllable inside existing systems.
- Data flows
- Process flows
- Decision points
- Release moments
- Roles
- AI workflows
Outcome
What does this deliver?
You receive an operational design in which process design, data flows, decision logic, release moments, roles and AI workflows come together. It makes visible how AI can reliably take part within existing processes, without losing control or transferability.
01
Process design
02
Data flow design
03
Decision logic
04
Release moments
05
Controllable AI workflows
06
Defined roles
Engagement
How does the engagement run?
- 01
Analysis
- 02
Process design
- 03
Data model
- 04
Decision points
- 05
Operational architecture
Practice
Common situations
- Document processing
- Intake processes
- Request processes
- Data validation
- Knowledge work
- Assessment and classification
Related services
Other routes within the Pientro approach.
Governance and oversight
How do you keep control over AI output?
Setting up ownership, release, monitoring, audit trail and escalation around AI workflows.
Read moreIntegration and operationalisation
How does AI become part of daily work?
Connecting AI workflows to existing systems, roles, data sources and ways of working.
Read moreContact
Design the operational foundation for AI.
Discuss with Pientro how process design, data flows, decision points and release moments should be set up before AI can reliably take part.